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avatar kingabzpro
/
Covid19-Vaccine-ML-Pipeline
mirror of https://github.com/kingabzpro/Covid19-Vaccine-ML-Pipeline.git

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  1. 08/19/2021 10:14:50 AM - INFO - automl_search.py: Generating pipelines to search over...
    2. 

  2. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    3. 

  3. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    4. 

  4. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    5. 

  5. 08/19/2021 10:14:51 AM - DEBUG - automl_search.py: allowed_estimators set to ['Decision Tree Classifier', 'LightGBM Classifier', 'Extra Trees Classifier', 'Elastic Net Classifier', 'CatBoost Classifier', 'XGBoost Classifier', 'Random Forest Classifier', 'Logistic Regression Classifier']
    6. 

  6. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    7. 

  7. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    8. 

  8. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    9. 

  9. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    10. 

  10. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    11. 

  11. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    12. 

  12. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    13. 

  13. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    14. 

  14. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    15. 

  15. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    16. 

  16. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    17. 

  17. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    18. 

  18. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    19. 

  19. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    20. 

  20. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    21. 

  21. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    22. 

  22. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    23. 

  23. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    24. 

  24. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    25. 

  25. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    26. 

  26. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    27. 

  27. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    28. 

  28. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    29. 

  29. 08/19/2021 10:14:51 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    30. 

  30. 08/19/2021 10:14:51 AM - INFO - automl_search.py: 8 pipelines ready for search.
    31. 

  31. 08/19/2021 10:14:51 AM - DEBUG - automl_search.py: allowed_pipelines set to ['Decision Tree Classifier w/ Imputer', 'LightGBM Classifier w/ Imputer', 'Extra Trees Classifier w/ Imputer', 'Elastic Net Classifier w/ Imputer + Standard Scaler', 'CatBoost Classifier w/ Imputer', 'XGBoost Classifier w/ Imputer', 'Random Forest Classifier w/ Imputer', 'Logistic Regression Classifier w/ Imputer + Standard Scaler']
    32. 

  32. 08/19/2021 10:14:51 AM - DEBUG - automl_search.py: allowed_model_families set to [ModelFamily.DECISION_TREE, ModelFamily.LIGHTGBM, ModelFamily.EXTRA_TREES, ModelFamily.LINEAR_MODEL, ModelFamily.XGBOOST, ModelFamily.RANDOM_FOREST, ModelFamily.CATBOOST]
    33. 

  33. 08/19/2021 10:14:51 AM - INFO - logger.py: 
    34. 

  34. *****************************
    35. 

  35. 08/19/2021 10:14:51 AM - INFO - logger.py: * Beginning pipeline search *
    36. 

  36. 08/19/2021 10:14:51 AM - INFO - logger.py: *****************************
    37. 

  37. 08/19/2021 10:14:51 AM - INFO - logger.py: 
    38. 

  38. 08/19/2021 10:14:51 AM - INFO - automl_search.py: Optimizing for Log Loss Binary. 
    39. 

  39. 08/19/2021 10:14:51 AM - INFO - automl_search.py: Lower score is better.
    40. 

  40. 

  41. 08/19/2021 10:14:51 AM - INFO - automl_search.py: Using SequentialEngine to train and score pipelines.
    42. 

  42. 08/19/2021 10:14:51 AM - INFO - automl_search.py: Will stop searching for new pipelines after 300 seconds.
    43. 

  43. 

  44. 08/19/2021 10:14:51 AM - INFO - automl_search.py: Allowed model families: decision_tree, lightgbm, extra_trees, linear_model, xgboost, random_forest, catboost
    45. 

  45. 

  46. 08/19/2021 10:14:52 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    47. 

  47. 08/19/2021 10:14:52 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    48. 

  48. 08/19/2021 10:14:52 AM - INFO - automl_search.py: Evaluating Baseline Pipeline: Mode Baseline Binary Classification Pipeline
    49. 

  49. 08/19/2021 10:14:54 AM - INFO - engine_base.py: Mode Baseline Binary Classification Pipeline:
    50. 

  50. 08/19/2021 10:14:54 AM - INFO - engine_base.py: 	Starting cross validation
    51. 

  51. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    52. 

  52. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    53. 

  53. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    54. 

  54. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.000)
    55. 

  55. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    56. 

  56. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 9.297
    57. 

  57. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    58. 

  58. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    59. 

  59. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    60. 

  60. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.000)
    61. 

  61. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    62. 

  62. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 9.306
    63. 

  63. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    64. 

  64. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    65. 

  65. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    66. 

  66. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.000)
    67. 

  67. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    68. 

  68. 08/19/2021 10:14:54 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 9.306
    69. 

  69. 08/19/2021 10:14:54 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 9.303
    70. 

  70. 08/19/2021 10:14:54 AM - INFO - logger.py: 
    71. 

  71. *****************************
    72. 

  72. 08/19/2021 10:14:54 AM - INFO - logger.py: * Evaluating Batch Number 1 *
    73. 

  73. 08/19/2021 10:14:54 AM - INFO - logger.py: *****************************
    74. 

  74. 08/19/2021 10:14:54 AM - INFO - logger.py: 
    75. 

  75. 08/19/2021 10:14:57 AM - INFO - engine_base.py: Elastic Net Classifier w/ Imputer + Standard Scaler:
    76. 

  76. 08/19/2021 10:14:57 AM - INFO - engine_base.py: 	Starting cross validation
    77. 

  77. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    78. 

  78. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    79. 

  79. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    80. 

  80. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.222)
    81. 

  81. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    82. 

  82. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.553
    83. 

  83. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    84. 

  84. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    85. 

  85. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    86. 

  86. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.220)
    87. 

  87. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    88. 

  88. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.555
    89. 

  89. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    90. 

  90. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    91. 

  91. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    92. 

  92. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.237)
    93. 

  93. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    94. 

  94. 08/19/2021 10:14:57 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.560
    95. 

  95. 08/19/2021 10:14:57 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.556
    96. 

  96. 08/19/2021 10:14:59 AM - INFO - engine_base.py: Decision Tree Classifier w/ Imputer:
    97. 

  97. 08/19/2021 10:14:59 AM - INFO - engine_base.py: 	Starting cross validation
    98. 

  98. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    99. 

  99. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    100. 

  100. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    101. 

  101. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.333)
    102. 

  102. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    103. 

  103. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.534
    104. 

  104. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    105. 

  105. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    106. 

  106. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    107. 

  107. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.329)
    108. 

  108. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    109. 

  109. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.633
    110. 

  110. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    111. 

  111. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    112. 

  112. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    113. 

  113. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.265)
    114. 

  114. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    115. 

  115. 08/19/2021 10:14:59 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.615
    116. 

  116. 08/19/2021 10:14:59 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.594
    117. 

  117. 08/19/2021 10:15:03 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    118. 

  118. 08/19/2021 10:15:03 AM - INFO - engine_base.py: 	Starting cross validation
    119. 

  119. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    120. 

  120. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    121. 

  121. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    122. 

  122. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.306)
    123. 

  123. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    124. 

  124. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.459
    125. 

  125. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    126. 

  126. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    127. 

  127. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    128. 

  128. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.317)
    129. 

  129. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    130. 

  130. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.462
    131. 

  131. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    132. 

  132. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    133. 

  133. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    134. 

  134. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.317)
    135. 

  135. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    136. 

  136. 08/19/2021 10:15:03 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.465
    137. 

  137. 08/19/2021 10:15:03 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.462
    138. 

  138. 08/19/2021 10:15:05 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    139. 

  139. 08/19/2021 10:15:05 AM - INFO - engine_base.py: 	Starting cross validation
    140. 

  140. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    141. 

  141. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    142. 

  142. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    143. 

  143. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.333)
    144. 

  144. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    145. 

  145. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.377
    146. 

  146. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    147. 

  147. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    148. 

  148. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    149. 

  149. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.343)
    150. 

  150. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    151. 

  151. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.379
    152. 

  152. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    153. 

  153. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    154. 

  154. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    155. 

  155. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.340)
    156. 

  156. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    157. 

  157. 08/19/2021 10:15:05 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.402
    158. 

  158. 08/19/2021 10:15:05 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.386
    159. 

  159. 08/19/2021 10:15:17 AM - INFO - automl_search.py: Exiting AutoMLSearch.
    160. 

  160. 08/19/2021 10:15:17 AM - INFO - automl_search.py: 
    161. 

  161. Search finished after 00:24            
    162. 

  162. 08/19/2021 10:15:18 AM - INFO - automl_search.py: Best pipeline: LightGBM Classifier w/ Imputer
    163. 

  163. 08/19/2021 10:15:18 AM - INFO - automl_search.py: Best pipeline Log Loss Binary: 0.385990
    164. 

  164. 08/19/2021 10:15:18 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    165. 

  165. 08/19/2021 10:15:18 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    166. 

  166. 08/19/2021 10:36:34 AM - INFO - automl_search.py: Generating pipelines to search over...
    167. 

  167. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    168. 

  168. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    169. 

  169. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    170. 

  170. 08/19/2021 10:36:35 AM - DEBUG - automl_search.py: allowed_estimators set to ['Decision Tree Classifier', 'LightGBM Classifier', 'Extra Trees Classifier', 'Elastic Net Classifier', 'CatBoost Classifier', 'XGBoost Classifier', 'Random Forest Classifier', 'Logistic Regression Classifier']
    171. 

  171. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    172. 

  172. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    173. 

  173. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    174. 

  174. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    175. 

  175. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    176. 

  176. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    177. 

  177. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    178. 

  178. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    179. 

  179. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    180. 

  180. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    181. 

  181. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    182. 

  182. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    183. 

  183. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    184. 

  184. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    185. 

  185. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    186. 

  186. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    187. 

  187. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    188. 

  188. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    189. 

  189. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    190. 

  190. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    191. 

  191. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    192. 

  192. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    193. 

  193. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    194. 

  194. 08/19/2021 10:36:35 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    195. 

  195. 08/19/2021 10:36:35 AM - INFO - automl_search.py: 8 pipelines ready for search.
    196. 

  196. 08/19/2021 10:36:35 AM - DEBUG - automl_search.py: allowed_pipelines set to ['Decision Tree Classifier w/ Imputer', 'LightGBM Classifier w/ Imputer', 'Extra Trees Classifier w/ Imputer', 'Elastic Net Classifier w/ Imputer + Standard Scaler', 'CatBoost Classifier w/ Imputer', 'XGBoost Classifier w/ Imputer', 'Random Forest Classifier w/ Imputer', 'Logistic Regression Classifier w/ Imputer + Standard Scaler']
    197. 

  197. 08/19/2021 10:36:35 AM - DEBUG - automl_search.py: allowed_model_families set to [ModelFamily.XGBOOST, ModelFamily.RANDOM_FOREST, ModelFamily.CATBOOST, ModelFamily.EXTRA_TREES, ModelFamily.LIGHTGBM, ModelFamily.DECISION_TREE, ModelFamily.LINEAR_MODEL]
    198. 

  198. 08/19/2021 10:36:35 AM - INFO - logger.py: 
    199. 

  199. *****************************
    200. 

  200. 08/19/2021 10:36:35 AM - INFO - logger.py: * Beginning pipeline search *
    201. 

  201. 08/19/2021 10:36:35 AM - INFO - logger.py: *****************************
    202. 

  202. 08/19/2021 10:36:35 AM - INFO - logger.py: 
    203. 

  203. 08/19/2021 10:36:35 AM - INFO - automl_search.py: Optimizing for Log Loss Binary. 
    204. 

  204. 08/19/2021 10:36:35 AM - INFO - automl_search.py: Lower score is better.
    205. 

  205. 

  206. 08/19/2021 10:36:35 AM - INFO - automl_search.py: Using SequentialEngine to train and score pipelines.
    207. 

  207. 08/19/2021 10:36:35 AM - INFO - automl_search.py: Will stop searching for new pipelines after 300 seconds.
    208. 

  208. 

  209. 08/19/2021 10:36:35 AM - INFO - automl_search.py: Allowed model families: xgboost, random_forest, catboost, extra_trees, lightgbm, decision_tree, linear_model
    210. 

  210. 

  211. 08/19/2021 10:36:36 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    212. 

  212. 08/19/2021 10:36:36 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    213. 

  213. 08/19/2021 10:36:36 AM - INFO - automl_search.py: Evaluating Baseline Pipeline: Mode Baseline Binary Classification Pipeline
    214. 

  214. 08/19/2021 10:36:38 AM - INFO - engine_base.py: Mode Baseline Binary Classification Pipeline:
    215. 

  215. 08/19/2021 10:36:38 AM - INFO - engine_base.py: 	Starting cross validation
    216. 

  216. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    217. 

  217. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    218. 

  218. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    219. 

  219. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.000)
    220. 

  220. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    221. 

  221. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 9.471
    222. 

  222. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    223. 

  223. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    224. 

  224. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    225. 

  225. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.000)
    226. 

  226. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    227. 

  227. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 9.471
    228. 

  228. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    229. 

  229. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    230. 

  230. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    231. 

  231. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.000)
    232. 

  232. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    233. 

  233. 08/19/2021 10:36:38 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 9.471
    234. 

  234. 08/19/2021 10:36:38 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 9.471
    235. 

  235. 08/19/2021 10:36:38 AM - INFO - logger.py: 
    236. 

  236. *****************************
    237. 

  237. 08/19/2021 10:36:38 AM - INFO - logger.py: * Evaluating Batch Number 1 *
    238. 

  238. 08/19/2021 10:36:38 AM - INFO - logger.py: *****************************
    239. 

  239. 08/19/2021 10:36:38 AM - INFO - logger.py: 
    240. 

  240. 08/19/2021 10:36:41 AM - INFO - engine_base.py: Elastic Net Classifier w/ Imputer + Standard Scaler:
    241. 

  241. 08/19/2021 10:36:41 AM - INFO - engine_base.py: 	Starting cross validation
    242. 

  242. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    243. 

  243. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    244. 

  244. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    245. 

  245. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.201)
    246. 

  246. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    247. 

  247. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.557
    248. 

  248. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    249. 

  249. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    250. 

  250. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    251. 

  251. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.236)
    252. 

  252. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    253. 

  253. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.558
    254. 

  254. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    255. 

  255. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    256. 

  256. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    257. 

  257. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.230)
    258. 

  258. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    259. 

  259. 08/19/2021 10:36:41 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.565
    260. 

  260. 08/19/2021 10:36:41 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.560
    261. 

  261. 08/19/2021 10:36:44 AM - INFO - engine_base.py: Decision Tree Classifier w/ Imputer:
    262. 

  262. 08/19/2021 10:36:44 AM - INFO - engine_base.py: 	Starting cross validation
    263. 

  263. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    264. 

  264. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    265. 

  265. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    266. 

  266. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (-0.000)
    267. 

  267. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    268. 

  268. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.651
    269. 

  269. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    270. 

  270. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    271. 

  271. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    272. 

  272. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (-0.000)
    273. 

  273. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    274. 

  274. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.555
    275. 

  275. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    276. 

  276. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    277. 

  277. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    278. 

  278. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (-0.000)
    279. 

  279. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    280. 

  280. 08/19/2021 10:36:44 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.585
    281. 

  281. 08/19/2021 10:36:44 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.597
    282. 

  282. 08/19/2021 10:36:48 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    283. 

  283. 08/19/2021 10:36:48 AM - INFO - engine_base.py: 	Starting cross validation
    284. 

  284. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    285. 

  285. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    286. 

  286. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    287. 

  287. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.297)
    288. 

  288. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    289. 

  289. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.454
    290. 

  290. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    291. 

  291. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    292. 

  292. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    293. 

  293. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.291)
    294. 

  294. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    295. 

  295. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.456
    296. 

  296. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    297. 

  297. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    298. 

  298. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    299. 

  299. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.314)
    300. 

  300. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    301. 

  301. 08/19/2021 10:36:48 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.470
    302. 

  302. 08/19/2021 10:36:48 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.460
    303. 

  303. 08/19/2021 10:36:50 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    304. 

  304. 08/19/2021 10:36:50 AM - INFO - engine_base.py: 	Starting cross validation
    305. 

  305. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    306. 

  306. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    307. 

  307. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    308. 

  308. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.322)
    309. 

  309. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    310. 

  310. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.382
    311. 

  311. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    312. 

  312. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    313. 

  313. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    314. 

  314. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.365)
    315. 

  315. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    316. 

  316. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.385
    317. 

  317. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    318. 

  318. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    319. 

  319. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    320. 

  320. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.377)
    321. 

  321. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    322. 

  322. 08/19/2021 10:36:50 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.401
    323. 

  323. 08/19/2021 10:36:50 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.389
    324. 

  324. 08/19/2021 10:36:54 AM - INFO - engine_base.py: Logistic Regression Classifier w/ Imputer + Standard Scaler:
    325. 

  325. 08/19/2021 10:36:54 AM - INFO - engine_base.py: 	Starting cross validation
    326. 

  326. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    327. 

  327. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    328. 

  328. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    329. 

  329. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.200)
    330. 

  330. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    331. 

  331. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.557
    332. 

  332. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    333. 

  333. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    334. 

  334. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    335. 

  335. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.236)
    336. 

  336. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    337. 

  337. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.558
    338. 

  338. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    339. 

  339. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    340. 

  340. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    341. 

  341. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.225)
    342. 

  342. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    343. 

  343. 08/19/2021 10:36:54 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.565
    344. 

  344. 08/19/2021 10:36:54 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.560
    345. 

  345. 08/19/2021 10:36:58 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    346. 

  346. 08/19/2021 10:36:58 AM - INFO - engine_base.py: 	Starting cross validation
    347. 

  347. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    348. 

  348. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    349. 

  349. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    350. 

  350. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.326)
    351. 

  351. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    352. 

  352. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.387
    353. 

  353. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    354. 

  354. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    355. 

  355. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    356. 

  356. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.321)
    357. 

  357. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    358. 

  358. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.390
    359. 

  359. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    360. 

  360. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    361. 

  361. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    362. 

  362. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.295)
    363. 

  363. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    364. 

  364. 08/19/2021 10:36:58 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.409
    365. 

  365. 08/19/2021 10:36:58 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.395
    366. 

  366. 08/19/2021 10:37:01 AM - INFO - engine_base.py: Extra Trees Classifier w/ Imputer:
    367. 

  367. 08/19/2021 10:37:01 AM - INFO - engine_base.py: 	Starting cross validation
    368. 

  368. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    369. 

  369. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    370. 

  370. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    371. 

  371. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.297)
    372. 

  372. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    373. 

  373. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.543
    374. 

  374. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    375. 

  375. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    376. 

  376. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    377. 

  377. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.287)
    378. 

  378. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    379. 

  379. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.544
    380. 

  380. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    381. 

  381. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    382. 

  382. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    383. 

  383. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.298)
    384. 

  384. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    385. 

  385. 08/19/2021 10:37:01 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.549
    386. 

  386. 08/19/2021 10:37:01 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.545
    387. 

  387. 08/19/2021 10:37:02 AM - INFO - engine_base.py: CatBoost Classifier w/ Imputer:
    388. 

  388. 08/19/2021 10:37:02 AM - INFO - engine_base.py: 	Starting cross validation
    389. 

  389. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    390. 

  390. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    391. 

  391. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    392. 

  392. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.442)
    393. 

  393. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    394. 

  394. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.627
    395. 

  395. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    396. 

  396. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    397. 

  397. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    398. 

  398. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.436)
    399. 

  399. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    400. 

  400. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.629
    401. 

  401. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    402. 

  402. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    403. 

  403. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    404. 

  404. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.435)
    405. 

  405. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    406. 

  406. 08/19/2021 10:37:02 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.629
    407. 

  407. 08/19/2021 10:37:02 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.628
    408. 

  408. 08/19/2021 10:37:03 AM - INFO - logger.py: 
    409. 

  409. *****************************
    410. 

  410. 08/19/2021 10:37:03 AM - INFO - logger.py: * Evaluating Batch Number 2 *
    411. 

  411. 08/19/2021 10:37:03 AM - INFO - logger.py: *****************************
    412. 

  412. 08/19/2021 10:37:03 AM - INFO - logger.py: 
    413. 

  413. 08/19/2021 10:37:05 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    414. 

  414. 08/19/2021 10:37:05 AM - INFO - engine_base.py: 	Starting cross validation
    415. 

  415. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    416. 

  416. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    417. 

  417. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    418. 

  418. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.227)
    419. 

  419. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    420. 

  420. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.476
    421. 

  421. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    422. 

  422. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    423. 

  423. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    424. 

  424. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.246)
    425. 

  425. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    426. 

  426. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.482
    427. 

  427. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    428. 

  428. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    429. 

  429. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    430. 

  430. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.349)
    431. 

  431. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    432. 

  432. 08/19/2021 10:37:05 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.493
    433. 

  433. 08/19/2021 10:37:05 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.484
    434. 

  434. 08/19/2021 10:37:07 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    435. 

  435. 08/19/2021 10:37:07 AM - INFO - engine_base.py: 	Starting cross validation
    436. 

  436. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    437. 

  437. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    438. 

  438. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    439. 

  439. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.264)
    440. 

  440. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    441. 

  441. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.515
    442. 

  442. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    443. 

  443. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    444. 

  444. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    445. 

  445. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.200)
    446. 

  446. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    447. 

  447. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.517
    448. 

  448. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    449. 

  449. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    450. 

  450. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    451. 

  451. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.242)
    452. 

  452. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    453. 

  453. 08/19/2021 10:37:07 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.526
    454. 

  454. 08/19/2021 10:37:07 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.519
    455. 

  455. 08/19/2021 10:37:09 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    456. 

  456. 08/19/2021 10:37:09 AM - INFO - engine_base.py: 	Starting cross validation
    457. 

  457. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    458. 

  458. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    459. 

  459. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    460. 

  460. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.259)
    461. 

  461. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    462. 

  462. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.489
    463. 

  463. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    464. 

  464. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    465. 

  465. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    466. 

  466. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.277)
    467. 

  467. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    468. 

  468. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.487
    469. 

  469. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    470. 

  470. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    471. 

  471. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    472. 

  472. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.253)
    473. 

  473. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    474. 

  474. 08/19/2021 10:37:09 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.497
    475. 

  475. 08/19/2021 10:37:09 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.491
    476. 

  476. 08/19/2021 10:37:10 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    477. 

  477. 08/19/2021 10:37:10 AM - INFO - engine_base.py: 	Starting cross validation
    478. 

  478. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    479. 

  479. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    480. 

  480. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    481. 

  481. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.434)
    482. 

  482. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    483. 

  483. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.593
    484. 

  484. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    485. 

  485. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    486. 

  486. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    487. 

  487. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.261)
    488. 

  488. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    489. 

  489. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.620
    490. 

  490. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    491. 

  491. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    492. 

  492. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    493. 

  493. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.213)
    494. 

  494. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    495. 

  495. 08/19/2021 10:37:11 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.613
    496. 

  496. 08/19/2021 10:37:11 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.609
    497. 

  497. 08/19/2021 10:37:13 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    498. 

  498. 08/19/2021 10:37:13 AM - INFO - engine_base.py: 	Starting cross validation
    499. 

  499. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    500. 

  500. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    501. 

  501. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    502. 

  502. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.367)
    503. 

  503. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    504. 

  504. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.401
    505. 

  505. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    506. 

  506. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    507. 

  507. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    508. 

  508. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.367)
    509. 

  509. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    510. 

  510. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.407
    511. 

  511. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    512. 

  512. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    513. 

  513. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    514. 

  514. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.383)
    515. 

  515. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    516. 

  516. 08/19/2021 10:37:13 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.424
    517. 

  517. 08/19/2021 10:37:13 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.411
    518. 

  518. 08/19/2021 10:37:13 AM - INFO - logger.py: 
    519. 

  519. *****************************
    520. 

  520. 08/19/2021 10:37:13 AM - INFO - logger.py: * Evaluating Batch Number 3 *
    521. 

  521. 08/19/2021 10:37:13 AM - INFO - logger.py: *****************************
    522. 

  522. 08/19/2021 10:37:13 AM - INFO - logger.py: 
    523. 

  523. 08/19/2021 10:37:21 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    524. 

  524. 08/19/2021 10:37:21 AM - INFO - engine_base.py: 	Starting cross validation
    525. 

  525. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    526. 

  526. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    527. 

  527. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    528. 

  528. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.149)
    529. 

  529. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    530. 

  530. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.634
    531. 

  531. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    532. 

  532. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    533. 

  533. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    534. 

  534. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.349)
    535. 

  535. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    536. 

  536. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.652
    537. 

  537. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    538. 

  538. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    539. 

  539. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    540. 

  540. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.220)
    541. 

  541. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    542. 

  542. 08/19/2021 10:37:21 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.652
    543. 

  543. 08/19/2021 10:37:21 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.646
    544. 

  544. 08/19/2021 10:37:32 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    545. 

  545. 08/19/2021 10:37:32 AM - INFO - engine_base.py: 	Starting cross validation
    546. 

  546. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    547. 

  547. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    548. 

  548. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    549. 

  549. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.100)
    550. 

  550. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    551. 

  551. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.593
    552. 

  552. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    553. 

  553. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    554. 

  554. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    555. 

  555. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.373)
    556. 

  556. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    557. 

  557. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.601
    558. 

  558. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    559. 

  559. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    560. 

  560. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    561. 

  561. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.267)
    562. 

  562. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    563. 

  563. 08/19/2021 10:37:32 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.623
    564. 

  564. 08/19/2021 10:37:32 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.606
    565. 

  565. 08/19/2021 10:37:55 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    566. 

  566. 08/19/2021 10:37:55 AM - INFO - engine_base.py: 	Starting cross validation
    567. 

  567. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    568. 

  568. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    569. 

  569. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    570. 

  570. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.326)
    571. 

  571. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    572. 

  572. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.558
    573. 

  573. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    574. 

  574. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    575. 

  575. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    576. 

  576. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.147)
    577. 

  577. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    578. 

  578. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.556
    579. 

  579. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    580. 

  580. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    581. 

  581. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    582. 

  582. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.156)
    583. 

  583. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    584. 

  584. 08/19/2021 10:37:55 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.585
    585. 

  585. 08/19/2021 10:37:55 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.567
    586. 

  586. 08/19/2021 10:38:08 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    587. 

  587. 08/19/2021 10:38:08 AM - INFO - engine_base.py: 	Starting cross validation
    588. 

  588. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    589. 

  589. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    590. 

  590. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    591. 

  591. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.322)
    592. 

  592. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    593. 

  593. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.450
    594. 

  594. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    595. 

  595. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    596. 

  596. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    597. 

  597. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.266)
    598. 

  598. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    599. 

  599. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.457
    600. 

  600. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    601. 

  601. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    602. 

  602. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    603. 

  603. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.270)
    604. 

  604. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    605. 

  605. 08/19/2021 10:38:08 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.471
    606. 

  606. 08/19/2021 10:38:08 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.459
    607. 

  607. 08/19/2021 10:38:12 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    608. 

  608. 08/19/2021 10:38:12 AM - INFO - engine_base.py: 	Starting cross validation
    609. 

  609. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    610. 

  610. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    611. 

  611. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    612. 

  612. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.257)
    613. 

  613. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    614. 

  614. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.502
    615. 

  615. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    616. 

  616. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    617. 

  617. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    618. 

  618. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.279)
    619. 

  619. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    620. 

  620. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.501
    621. 

  621. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    622. 

  622. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    623. 

  623. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    624. 

  624. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.276)
    625. 

  625. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    626. 

  626. 08/19/2021 10:38:12 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.513
    627. 

  627. 08/19/2021 10:38:12 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.506
    628. 

  628. 08/19/2021 10:38:12 AM - INFO - logger.py: 
    629. 

  629. *****************************
    630. 

  630. 08/19/2021 10:38:12 AM - INFO - logger.py: * Evaluating Batch Number 4 *
    631. 

  631. 08/19/2021 10:38:12 AM - INFO - logger.py: *****************************
    632. 

  632. 08/19/2021 10:38:12 AM - INFO - logger.py: 
    633. 

  633. 08/19/2021 10:38:41 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    634. 

  634. 08/19/2021 10:38:41 AM - INFO - engine_base.py: 	Starting cross validation
    635. 

  635. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    636. 

  636. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    637. 

  637. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    638. 

  638. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.266)
    639. 

  639. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    640. 

  640. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.500
    641. 

  641. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    642. 

  642. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    643. 

  643. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    644. 

  644. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.267)
    645. 

  645. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    646. 

  646. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.502
    647. 

  647. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    648. 

  648. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    649. 

  649. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    650. 

  650. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.309)
    651. 

  651. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    652. 

  652. 08/19/2021 10:38:41 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.511
    653. 

  653. 08/19/2021 10:38:41 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.504
    654. 

  654. 08/19/2021 10:39:00 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    655. 

  655. 08/19/2021 10:39:00 AM - INFO - engine_base.py: 	Starting cross validation
    656. 

  656. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    657. 

  657. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    658. 

  658. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    659. 

  659. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.277)
    660. 

  660. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    661. 

  661. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.549
    662. 

  662. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    663. 

  663. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    664. 

  664. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    665. 

  665. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.269)
    666. 

  666. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    667. 

  667. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.549
    668. 

  668. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    669. 

  669. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    670. 

  670. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    671. 

  671. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.264)
    672. 

  672. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    673. 

  673. 08/19/2021 10:39:00 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.553
    674. 

  674. 08/19/2021 10:39:00 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.550
    675. 

  675. 08/19/2021 10:39:41 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    676. 

  676. 08/19/2021 10:39:41 AM - INFO - engine_base.py: 	Starting cross validation
    677. 

  677. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    678. 

  678. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    679. 

  679. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    680. 

  680. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.293)
    681. 

  681. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    682. 

  682. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.475
    683. 

  683. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    684. 

  684. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    685. 

  685. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    686. 

  686. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.274)
    687. 

  687. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    688. 

  688. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.478
    689. 

  689. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    690. 

  690. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    691. 

  691. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    692. 

  692. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.317)
    693. 

  693. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    694. 

  694. 08/19/2021 10:39:41 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.490
    695. 

  695. 08/19/2021 10:39:41 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.481
    696. 

  696. 08/19/2021 10:40:10 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    697. 

  697. 08/19/2021 10:40:10 AM - INFO - engine_base.py: 	Starting cross validation
    698. 

  698. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    699. 

  699. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    700. 

  700. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    701. 

  701. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.280)
    702. 

  702. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    703. 

  703. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.549
    704. 

  704. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    705. 

  705. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    706. 

  706. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    707. 

  707. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.263)
    708. 

  708. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    709. 

  709. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.549
    710. 

  710. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    711. 

  711. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    712. 

  712. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    713. 

  713. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.268)
    714. 

  714. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    715. 

  715. 08/19/2021 10:40:10 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.554
    716. 

  716. 08/19/2021 10:40:10 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.551
    717. 

  717. 08/19/2021 10:40:51 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    718. 

  718. 08/19/2021 10:40:51 AM - INFO - engine_base.py: 	Starting cross validation
    719. 

  719. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    720. 

  720. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    721. 

  721. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    722. 

  722. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.297)
    723. 

  723. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    724. 

  724. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.475
    725. 

  725. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    726. 

  726. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    727. 

  727. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    728. 

  728. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.271)
    729. 

  729. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    730. 

  730. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.478
    731. 

  731. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    732. 

  732. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    733. 

  733. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    734. 

  734. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.313)
    735. 

  735. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    736. 

  736. 08/19/2021 10:40:51 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.489
    737. 

  737. 08/19/2021 10:40:51 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.481
    738. 

  738. 08/19/2021 10:40:51 AM - INFO - logger.py: 
    739. 

  739. *****************************
    740. 

  740. 08/19/2021 10:40:51 AM - INFO - logger.py: * Evaluating Batch Number 5 *
    741. 

  741. 08/19/2021 10:40:51 AM - INFO - logger.py: *****************************
    742. 

  742. 08/19/2021 10:40:51 AM - INFO - logger.py: 
    743. 

  743. 08/19/2021 10:41:18 AM - INFO - engine_base.py: Extra Trees Classifier w/ Imputer:
    744. 

  744. 08/19/2021 10:41:18 AM - INFO - engine_base.py: 	Starting cross validation
    745. 

  745. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    746. 

  746. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    747. 

  747. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    748. 

  748. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.293)
    749. 

  749. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    750. 

  750. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.553
    751. 

  751. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    752. 

  752. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    753. 

  753. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    754. 

  754. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.288)
    755. 

  755. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    756. 

  756. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.553
    757. 

  757. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    758. 

  758. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    759. 

  759. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    760. 

  760. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.299)
    761. 

  761. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    762. 

  762. 08/19/2021 10:41:19 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.558
    763. 

  763. 08/19/2021 10:41:19 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.555
    764. 

  764. 08/19/2021 10:41:38 AM - INFO - engine_base.py: Extra Trees Classifier w/ Imputer:
    765. 

  765. 08/19/2021 10:41:38 AM - INFO - engine_base.py: 	Starting cross validation
    766. 

  766. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    767. 

  767. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    768. 

  768. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    769. 

  769. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.291)
    770. 

  770. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    771. 

  771. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.562
    772. 

  772. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    773. 

  773. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    774. 

  774. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    775. 

  775. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.291)
    776. 

  776. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    777. 

  777. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.562
    778. 

  778. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    779. 

  779. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    780. 

  780. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    781. 

  781. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.289)
    782. 

  782. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    783. 

  783. 08/19/2021 10:41:38 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.565
    784. 

  784. 08/19/2021 10:41:38 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.563
    785. 

  785. 08/19/2021 10:41:39 AM - INFO - automl_search.py: 
    786. 

  786. Search finished after 05:02            
    787. 

  787. 08/19/2021 10:41:40 AM - INFO - automl_search.py: Best pipeline: LightGBM Classifier w/ Imputer
    788. 

  788. 08/19/2021 10:41:40 AM - INFO - automl_search.py: Best pipeline Log Loss Binary: 0.389436
    789. 

  789. 08/19/2021 10:41:40 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    790. 

  790. 08/19/2021 10:41:41 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    791. 

  791. 08/19/2021 10:41:41 AM - INFO - automl_search.py: Generating pipelines to search over...
    792. 

  792. 08/19/2021 10:41:41 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    793. 

  793. 08/19/2021 10:41:41 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    794. 

  794. 08/19/2021 10:41:41 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    795. 

  795. 08/19/2021 10:41:41 AM - DEBUG - automl_search.py: allowed_estimators set to ['Decision Tree Classifier', 'LightGBM Classifier', 'Extra Trees Classifier', 'Elastic Net Classifier', 'CatBoost Classifier', 'XGBoost Classifier', 'Random Forest Classifier', 'Logistic Regression Classifier']
    796. 

  796. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    797. 

  797. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    798. 

  798. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    799. 

  799. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    800. 

  800. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    801. 

  801. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    802. 

  802. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    803. 

  803. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    804. 

  804. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    805. 

  805. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    806. 

  806. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    807. 

  807. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    808. 

  808. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    809. 

  809. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    810. 

  810. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    811. 

  811. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    812. 

  812. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    813. 

  813. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    814. 

  814. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    815. 

  815. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    816. 

  816. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    817. 

  817. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    818. 

  818. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    819. 

  819. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    820. 

  820. 08/19/2021 10:41:42 AM - INFO - automl_search.py: 8 pipelines ready for search.
    821. 

  821. 08/19/2021 10:41:42 AM - DEBUG - automl_search.py: allowed_pipelines set to ['Decision Tree Classifier w/ Imputer', 'LightGBM Classifier w/ Imputer', 'Extra Trees Classifier w/ Imputer', 'Elastic Net Classifier w/ Imputer + Standard Scaler', 'CatBoost Classifier w/ Imputer', 'XGBoost Classifier w/ Imputer', 'Random Forest Classifier w/ Imputer', 'Logistic Regression Classifier w/ Imputer + Standard Scaler']
    822. 

  822. 08/19/2021 10:41:42 AM - DEBUG - automl_search.py: allowed_model_families set to [ModelFamily.XGBOOST, ModelFamily.RANDOM_FOREST, ModelFamily.CATBOOST, ModelFamily.EXTRA_TREES, ModelFamily.LIGHTGBM, ModelFamily.DECISION_TREE, ModelFamily.LINEAR_MODEL]
    823. 

  823. 08/19/2021 10:41:42 AM - INFO - logger.py: 
    824. 

  824. *****************************
    825. 

  825. 08/19/2021 10:41:42 AM - INFO - logger.py: * Beginning pipeline search *
    826. 

  826. 08/19/2021 10:41:42 AM - INFO - logger.py: *****************************
    827. 

  827. 08/19/2021 10:41:42 AM - INFO - logger.py: 
    828. 

  828. 08/19/2021 10:41:42 AM - INFO - automl_search.py: Optimizing for Log Loss Binary. 
    829. 

  829. 08/19/2021 10:41:42 AM - INFO - automl_search.py: Lower score is better.
    830. 

  830. 

  831. 08/19/2021 10:41:42 AM - INFO - automl_search.py: Using SequentialEngine to train and score pipelines.
    832. 

  832. 08/19/2021 10:41:42 AM - INFO - automl_search.py: Will stop searching for new pipelines after 300 seconds.
    833. 

  833. 

  834. 08/19/2021 10:41:42 AM - INFO - automl_search.py: Allowed model families: xgboost, random_forest, catboost, extra_trees, lightgbm, decision_tree, linear_model
    835. 

  835. 

  836. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    837. 

  837. 08/19/2021 10:41:42 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    838. 

  838. 08/19/2021 10:41:42 AM - INFO - automl_search.py: Evaluating Baseline Pipeline: Mode Baseline Binary Classification Pipeline
    839. 

  839. 08/19/2021 10:41:46 AM - INFO - engine_base.py: Mode Baseline Binary Classification Pipeline:
    840. 

  840. 08/19/2021 10:41:46 AM - INFO - engine_base.py: 	Starting cross validation
    841. 

  841. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    842. 

  842. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    843. 

  843. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    844. 

  844. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.000)
    845. 

  845. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    846. 

  846. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 9.306
    847. 

  847. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    848. 

  848. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    849. 

  849. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    850. 

  850. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.000)
    851. 

  851. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    852. 

  852. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 9.306
    853. 

  853. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    854. 

  854. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    855. 

  855. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    856. 

  856. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.000)
    857. 

  857. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    858. 

  858. 08/19/2021 10:41:46 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 9.315
    859. 

  859. 08/19/2021 10:41:46 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 9.309
    860. 

  860. 08/19/2021 10:41:46 AM - INFO - logger.py: 
    861. 

  861. *****************************
    862. 

  862. 08/19/2021 10:41:46 AM - INFO - logger.py: * Evaluating Batch Number 1 *
    863. 

  863. 08/19/2021 10:41:46 AM - INFO - logger.py: *****************************
    864. 

  864. 08/19/2021 10:41:46 AM - INFO - logger.py: 
    865. 

  865. 08/19/2021 10:41:53 AM - INFO - engine_base.py: Elastic Net Classifier w/ Imputer + Standard Scaler:
    866. 

  866. 08/19/2021 10:41:53 AM - INFO - engine_base.py: 	Starting cross validation
    867. 

  867. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    868. 

  868. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    869. 

  869. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    870. 

  870. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.203)
    871. 

  871. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    872. 

  872. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.557
    873. 

  873. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    874. 

  874. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    875. 

  875. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    876. 

  876. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.239)
    877. 

  877. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    878. 

  878. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.555
    879. 

  879. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    880. 

  880. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    881. 

  881. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    882. 

  882. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.241)
    883. 

  883. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    884. 

  884. 08/19/2021 10:41:53 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.554
    885. 

  885. 08/19/2021 10:41:53 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.556
    886. 

  886. 08/19/2021 10:41:57 AM - INFO - engine_base.py: Decision Tree Classifier w/ Imputer:
    887. 

  887. 08/19/2021 10:41:57 AM - INFO - engine_base.py: 	Starting cross validation
    888. 

  888. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    889. 

  889. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    890. 

  890. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    891. 

  891. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (-0.000)
    892. 

  892. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    893. 

  893. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.551
    894. 

  894. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    895. 

  895. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    896. 

  896. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    897. 

  897. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.280)
    898. 

  898. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    899. 

  899. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.583
    900. 

  900. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    901. 

  901. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    902. 

  902. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    903. 

  903. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.288)
    904. 

  904. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    905. 

  905. 08/19/2021 10:41:57 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.547
    906. 

  906. 08/19/2021 10:41:57 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.560
    907. 

  907. 08/19/2021 10:42:07 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    908. 

  908. 08/19/2021 10:42:07 AM - INFO - engine_base.py: 	Starting cross validation
    909. 

  909. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    910. 

  910. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    911. 

  911. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    912. 

  912. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.324)
    913. 

  913. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    914. 

  914. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.462
    915. 

  915. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    916. 

  916. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    917. 

  917. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    918. 

  918. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.302)
    919. 

  919. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    920. 

  920. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.464
    921. 

  921. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    922. 

  922. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    923. 

  923. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    924. 

  924. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.349)
    925. 

  925. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    926. 

  926. 08/19/2021 10:42:07 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.454
    927. 

  927. 08/19/2021 10:42:07 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.460
    928. 

  928. 08/19/2021 10:42:11 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    929. 

  929. 08/19/2021 10:42:11 AM - INFO - engine_base.py: 	Starting cross validation
    930. 

  930. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    931. 

  931. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    932. 

  932. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    933. 

  933. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.295)
    934. 

  934. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    935. 

  935. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.404
    936. 

  936. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    937. 

  937. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    938. 

  938. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    939. 

  939. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.346)
    940. 

  940. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    941. 

  941. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.399
    942. 

  942. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    943. 

  943. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    944. 

  944. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    945. 

  945. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.355)
    946. 

  946. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    947. 

  947. 08/19/2021 10:42:11 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.383
    948. 

  948. 08/19/2021 10:42:11 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.395
    949. 

  949. 08/19/2021 10:42:20 AM - INFO - engine_base.py: Logistic Regression Classifier w/ Imputer + Standard Scaler:
    950. 

  950. 08/19/2021 10:42:20 AM - INFO - engine_base.py: 	Starting cross validation
    951. 

  951. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    952. 

  952. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    953. 

  953. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    954. 

  954. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.203)
    955. 

  955. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    956. 

  956. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.557
    957. 

  957. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    958. 

  958. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    959. 

  959. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    960. 

  960. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.233)
    961. 

  961. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    962. 

  962. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.555
    963. 

  963. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    964. 

  964. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    965. 

  965. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    966. 

  966. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.241)
    967. 

  967. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    968. 

  968. 08/19/2021 10:42:20 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.554
    969. 

  969. 08/19/2021 10:42:20 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.555
    970. 

  970. 08/19/2021 10:42:30 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    971. 

  971. 08/19/2021 10:42:30 AM - INFO - engine_base.py: 	Starting cross validation
    972. 

  972. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    973. 

  973. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    974. 

  974. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    975. 

  975. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.302)
    976. 

  976. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    977. 

  977. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.408
    978. 

  978. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    979. 

  979. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    980. 

  980. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    981. 

  981. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.312)
    982. 

  982. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    983. 

  983. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.398
    984. 

  984. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    985. 

  985. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    986. 

  986. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    987. 

  987. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.354)
    988. 

  988. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    989. 

  989. 08/19/2021 10:42:31 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.389
    990. 

  990. 08/19/2021 10:42:31 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.398
    991. 

  991. 08/19/2021 10:42:37 AM - INFO - engine_base.py: Extra Trees Classifier w/ Imputer:
    992. 

  992. 08/19/2021 10:42:37 AM - INFO - engine_base.py: 	Starting cross validation
    993. 

  993. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    994. 

  994. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    995. 

  995. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    996. 

  996. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.297)
    997. 

  997. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    998. 

  998. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.540
    999. 

  999. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1000. 

  1000. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1001. 

  1001. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1002. 

  1002. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.299)
    1003. 

  1003. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1004. 

  1004. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.540
    1005. 

  1005. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1006. 

  1006. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1007. 

  1007. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1008. 

  1008. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.293)
    1009. 

  1009. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1010. 

  1010. 08/19/2021 10:42:37 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.539
    1011. 

  1011. 08/19/2021 10:42:37 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.540
    1012. 

  1012. 08/19/2021 10:42:39 AM - INFO - engine_base.py: CatBoost Classifier w/ Imputer:
    1013. 

  1013. 08/19/2021 10:42:39 AM - INFO - engine_base.py: 	Starting cross validation
    1014. 

  1014. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1015. 

  1015. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1016. 

  1016. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1017. 

  1017. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.438)
    1018. 

  1018. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1019. 

  1019. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.626
    1020. 

  1020. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1021. 

  1021. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1022. 

  1022. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1023. 

  1023. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.432)
    1024. 

  1024. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1025. 

  1025. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.627
    1026. 

  1026. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1027. 

  1027. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1028. 

  1028. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1029. 

  1029. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.444)
    1030. 

  1030. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1031. 

  1031. 08/19/2021 10:42:39 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.628
    1032. 

  1032. 08/19/2021 10:42:39 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.627
    1033. 

  1033. 08/19/2021 10:42:39 AM - INFO - logger.py: 
    1034. 

  1034. *****************************
    1035. 

  1035. 08/19/2021 10:42:39 AM - INFO - logger.py: * Evaluating Batch Number 2 *
    1036. 

  1036. 08/19/2021 10:42:39 AM - INFO - logger.py: *****************************
    1037. 

  1037. 08/19/2021 10:42:39 AM - INFO - logger.py: 
    1038. 

  1038. 08/19/2021 10:42:42 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1039. 

  1039. 08/19/2021 10:42:42 AM - INFO - engine_base.py: 	Starting cross validation
    1040. 

  1040. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1041. 

  1041. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1042. 

  1042. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1043. 

  1043. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.310)
    1044. 

  1044. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1045. 

  1045. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.489
    1046. 

  1046. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1047. 

  1047. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1048. 

  1048. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1049. 

  1049. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.284)
    1050. 

  1050. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1051. 

  1051. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.489
    1052. 

  1052. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1053. 

  1053. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1054. 

  1054. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1055. 

  1055. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.310)
    1056. 

  1056. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1057. 

  1057. 08/19/2021 10:42:42 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.478
    1058. 

  1058. 08/19/2021 10:42:42 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.485
    1059. 

  1059. 08/19/2021 10:42:45 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1060. 

  1060. 08/19/2021 10:42:45 AM - INFO - engine_base.py: 	Starting cross validation
    1061. 

  1061. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1062. 

  1062. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1063. 

  1063. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1064. 

  1064. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.218)
    1065. 

  1065. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1066. 

  1066. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.522
    1067. 

  1067. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1068. 

  1068. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1069. 

  1069. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1070. 

  1070. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.268)
    1071. 

  1071. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1072. 

  1072. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.520
    1073. 

  1073. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1074. 

  1074. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1075. 

  1075. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1076. 

  1076. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.265)
    1077. 

  1077. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1078. 

  1078. 08/19/2021 10:42:45 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.515
    1079. 

  1079. 08/19/2021 10:42:45 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.519
    1080. 

  1080. 08/19/2021 10:42:48 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1081. 

  1081. 08/19/2021 10:42:48 AM - INFO - engine_base.py: 	Starting cross validation
    1082. 

  1082. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1083. 

  1083. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1084. 

  1084. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1085. 

  1085. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.276)
    1086. 

  1086. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1087. 

  1087. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.491
    1088. 

  1088. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1089. 

  1089. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1090. 

  1090. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1091. 

  1091. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.285)
    1092. 

  1092. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1093. 

  1093. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.493
    1094. 

  1094. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1095. 

  1095. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1096. 

  1096. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1097. 

  1097. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.307)
    1098. 

  1098. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1099. 

  1099. 08/19/2021 10:42:48 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.486
    1100. 

  1100. 08/19/2021 10:42:48 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.490
    1101. 

  1101. 08/19/2021 10:42:51 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1102. 

  1102. 08/19/2021 10:42:51 AM - INFO - engine_base.py: 	Starting cross validation
    1103. 

  1103. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1104. 

  1104. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1105. 

  1105. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1106. 

  1106. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.291)
    1107. 

  1107. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1108. 

  1108. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.651
    1109. 

  1109. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1110. 

  1110. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1111. 

  1111. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1112. 

  1112. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.250)
    1113. 

  1113. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1114. 

  1114. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.616
    1115. 

  1115. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1116. 

  1116. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1117. 

  1117. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1118. 

  1118. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.233)
    1119. 

  1119. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1120. 

  1120. 08/19/2021 10:42:51 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.601
    1121. 

  1121. 08/19/2021 10:42:51 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.622
    1122. 

  1122. 08/19/2021 10:42:55 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1123. 

  1123. 08/19/2021 10:42:55 AM - INFO - engine_base.py: 	Starting cross validation
    1124. 

  1124. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1125. 

  1125. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1126. 

  1126. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1127. 

  1127. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.323)
    1128. 

  1128. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1129. 

  1129. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.417
    1130. 

  1130. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1131. 

  1131. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1132. 

  1132. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1133. 

  1133. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.271)
    1134. 

  1134. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1135. 

  1135. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.412
    1136. 

  1136. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1137. 

  1137. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1138. 

  1138. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1139. 

  1139. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.358)
    1140. 

  1140. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1141. 

  1141. 08/19/2021 10:42:55 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.400
    1142. 

  1142. 08/19/2021 10:42:55 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.409
    1143. 

  1143. 08/19/2021 10:42:55 AM - INFO - logger.py: 
    1144. 

  1144. *****************************
    1145. 

  1145. 08/19/2021 10:42:55 AM - INFO - logger.py: * Evaluating Batch Number 3 *
    1146. 

  1146. 08/19/2021 10:42:55 AM - INFO - logger.py: *****************************
    1147. 

  1147. 08/19/2021 10:42:55 AM - INFO - logger.py: 
    1148. 

  1148. 08/19/2021 10:43:06 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    1149. 

  1149. 08/19/2021 10:43:06 AM - INFO - engine_base.py: 	Starting cross validation
    1150. 

  1150. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1151. 

  1151. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1152. 

  1152. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1153. 

  1153. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.159)
    1154. 

  1154. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1155. 

  1155. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.653
    1156. 

  1156. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1157. 

  1157. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1158. 

  1158. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1159. 

  1159. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.112)
    1160. 

  1160. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1161. 

  1161. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.667
    1162. 

  1162. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1163. 

  1163. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1164. 

  1164. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1165. 

  1165. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.367)
    1166. 

  1166. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1167. 

  1167. 08/19/2021 10:43:06 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.630
    1168. 

  1168. 08/19/2021 10:43:06 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.650
    1169. 

  1169. 08/19/2021 10:43:14 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    1170. 

  1170. 08/19/2021 10:43:14 AM - INFO - engine_base.py: 	Starting cross validation
    1171. 

  1171. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1172. 

  1172. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1173. 

  1173. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1174. 

  1174. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.127)
    1175. 

  1175. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1176. 

  1176. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.633
    1177. 

  1177. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1178. 

  1178. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1179. 

  1179. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1180. 

  1180. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.079)
    1181. 

  1181. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1182. 

  1182. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.611
    1183. 

  1183. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1184. 

  1184. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1185. 

  1185. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1186. 

  1186. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.224)
    1187. 

  1187. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1188. 

  1188. 08/19/2021 10:43:14 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.591
    1189. 

  1189. 08/19/2021 10:43:14 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.612
    1190. 

  1190. 08/19/2021 10:43:31 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    1191. 

  1191. 08/19/2021 10:43:31 AM - INFO - engine_base.py: 	Starting cross validation
    1192. 

  1192. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1193. 

  1193. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1194. 

  1194. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1195. 

  1195. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.207)
    1196. 

  1196. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1197. 

  1197. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.591
    1198. 

  1198. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1199. 

  1199. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1200. 

  1200. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1201. 

  1201. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.316)
    1202. 

  1202. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1203. 

  1203. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.577
    1204. 

  1204. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1205. 

  1205. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1206. 

  1206. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1207. 

  1207. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.222)
    1208. 

  1208. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1209. 

  1209. 08/19/2021 10:43:31 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.558
    1210. 

  1210. 08/19/2021 10:43:31 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.575
    1211. 

  1211. 08/19/2021 10:43:48 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    1212. 

  1212. 08/19/2021 10:43:48 AM - INFO - engine_base.py: 	Starting cross validation
    1213. 

  1213. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1214. 

  1214. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1215. 

  1215. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1216. 

  1216. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.287)
    1217. 

  1217. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1218. 

  1218. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.461
    1219. 

  1219. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1220. 

  1220. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1221. 

  1221. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1222. 

  1222. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.377)
    1223. 

  1223. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1224. 

  1224. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.461
    1225. 

  1225. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1226. 

  1226. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1227. 

  1227. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1228. 

  1228. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.316)
    1229. 

  1229. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1230. 

  1230. 08/19/2021 10:43:48 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.453
    1231. 

  1231. 08/19/2021 10:43:48 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.458
    1232. 

  1232. 08/19/2021 10:43:52 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    1233. 

  1233. 08/19/2021 10:43:52 AM - INFO - engine_base.py: 	Starting cross validation
    1234. 

  1234. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1235. 

  1235. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1236. 

  1236. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1237. 

  1237. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.271)
    1238. 

  1238. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1239. 

  1239. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.504
    1240. 

  1240. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1241. 

  1241. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1242. 

  1242. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1243. 

  1243. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.237)
    1244. 

  1244. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1245. 

  1245. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.505
    1246. 

  1246. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1247. 

  1247. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1248. 

  1248. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1249. 

  1249. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.278)
    1250. 

  1250. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1251. 

  1251. 08/19/2021 10:43:52 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.495
    1252. 

  1252. 08/19/2021 10:43:52 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.501
    1253. 

  1253. 08/19/2021 10:43:52 AM - INFO - logger.py: 
    1254. 

  1254. *****************************
    1255. 

  1255. 08/19/2021 10:43:52 AM - INFO - logger.py: * Evaluating Batch Number 4 *
    1256. 

  1256. 08/19/2021 10:43:52 AM - INFO - logger.py: *****************************
    1257. 

  1257. 08/19/2021 10:43:52 AM - INFO - logger.py: 
    1258. 

  1258. 08/19/2021 10:44:21 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    1259. 

  1259. 08/19/2021 10:44:21 AM - INFO - engine_base.py: 	Starting cross validation
    1260. 

  1260. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1261. 

  1261. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1262. 

  1262. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1263. 

  1263. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.292)
    1264. 

  1264. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1265. 

  1265. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.505
    1266. 

  1266. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1267. 

  1267. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1268. 

  1268. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1269. 

  1269. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.266)
    1270. 

  1270. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1271. 

  1271. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.505
    1272. 

  1272. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1273. 

  1273. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1274. 

  1274. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1275. 

  1275. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.293)
    1276. 

  1276. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1277. 

  1277. 08/19/2021 10:44:21 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.498
    1278. 

  1278. 08/19/2021 10:44:21 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.503
    1279. 

  1279. 08/19/2021 10:44:37 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    1280. 

  1280. 08/19/2021 10:44:37 AM - INFO - engine_base.py: 	Starting cross validation
    1281. 

  1281. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1282. 

  1282. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1283. 

  1283. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1284. 

  1284. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.278)
    1285. 

  1285. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1286. 

  1286. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.548
    1287. 

  1287. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1288. 

  1288. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1289. 

  1289. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1290. 

  1290. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.269)
    1291. 

  1291. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1292. 

  1292. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.548
    1293. 

  1293. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1294. 

  1294. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1295. 

  1295. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1296. 

  1296. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.264)
    1297. 

  1297. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1298. 

  1298. 08/19/2021 10:44:37 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.545
    1299. 

  1299. 08/19/2021 10:44:37 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.547
    1300. 

  1300. 08/19/2021 10:45:13 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    1301. 

  1301. 08/19/2021 10:45:13 AM - INFO - engine_base.py: 	Starting cross validation
    1302. 

  1302. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1303. 

  1303. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1304. 

  1304. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1305. 

  1305. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.308)
    1306. 

  1306. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1307. 

  1307. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.483
    1308. 

  1308. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1309. 

  1309. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1310. 

  1310. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1311. 

  1311. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.265)
    1312. 

  1312. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1313. 

  1313. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.483
    1314. 

  1314. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1315. 

  1315. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1316. 

  1316. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1317. 

  1317. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.294)
    1318. 

  1318. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1319. 

  1319. 08/19/2021 10:45:13 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.476
    1320. 

  1320. 08/19/2021 10:45:13 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.481
    1321. 

  1321. 08/19/2021 10:45:37 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    1322. 

  1322. 08/19/2021 10:45:37 AM - INFO - engine_base.py: 	Starting cross validation
    1323. 

  1323. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1324. 

  1324. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1325. 

  1325. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1326. 

  1326. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.277)
    1327. 

  1327. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1328. 

  1328. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.548
    1329. 

  1329. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1330. 

  1330. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1331. 

  1331. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1332. 

  1332. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.272)
    1333. 

  1333. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1334. 

  1334. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.548
    1335. 

  1335. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1336. 

  1336. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1337. 

  1337. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1338. 

  1338. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.269)
    1339. 

  1339. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1340. 

  1340. 08/19/2021 10:45:37 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.545
    1341. 

  1341. 08/19/2021 10:45:37 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.547
    1342. 

  1342. 08/19/2021 10:46:14 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    1343. 

  1343. 08/19/2021 10:46:14 AM - INFO - engine_base.py: 	Starting cross validation
    1344. 

  1344. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1345. 

  1345. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1346. 

  1346. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1347. 

  1347. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.292)
    1348. 

  1348. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1349. 

  1349. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.483
    1350. 

  1350. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1351. 

  1351. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1352. 

  1352. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1353. 

  1353. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.284)
    1354. 

  1354. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1355. 

  1355. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.483
    1356. 

  1356. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1357. 

  1357. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1358. 

  1358. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1359. 

  1359. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.292)
    1360. 

  1360. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1361. 

  1361. 08/19/2021 10:46:14 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.476
    1362. 

  1362. 08/19/2021 10:46:14 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.480
    1363. 

  1363. 08/19/2021 10:46:14 AM - INFO - logger.py: 
    1364. 

  1364. *****************************
    1365. 

  1365. 08/19/2021 10:46:14 AM - INFO - logger.py: * Evaluating Batch Number 5 *
    1366. 

  1366. 08/19/2021 10:46:14 AM - INFO - logger.py: *****************************
    1367. 

  1367. 08/19/2021 10:46:14 AM - INFO - logger.py: 
    1368. 

  1368. 08/19/2021 10:46:38 AM - INFO - engine_base.py: Extra Trees Classifier w/ Imputer:
    1369. 

  1369. 08/19/2021 10:46:38 AM - INFO - engine_base.py: 	Starting cross validation
    1370. 

  1370. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1371. 

  1371. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1372. 

  1372. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1373. 

  1373. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.292)
    1374. 

  1374. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1375. 

  1375. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.550
    1376. 

  1376. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1377. 

  1377. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1378. 

  1378. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1379. 

  1379. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.290)
    1380. 

  1380. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1381. 

  1381. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.550
    1382. 

  1382. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1383. 

  1383. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1384. 

  1384. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1385. 

  1385. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.289)
    1386. 

  1386. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1387. 

  1387. 08/19/2021 10:46:38 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.550
    1388. 

  1388. 08/19/2021 10:46:38 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.550
    1389. 

  1389. 08/19/2021 10:46:56 AM - INFO - engine_base.py: Extra Trees Classifier w/ Imputer:
    1390. 

  1390. 08/19/2021 10:46:56 AM - INFO - engine_base.py: 	Starting cross validation
    1391. 

  1391. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1392. 

  1392. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1393. 

  1393. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1394. 

  1394. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.281)
    1395. 

  1395. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1396. 

  1396. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.559
    1397. 

  1397. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1398. 

  1398. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1399. 

  1399. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1400. 

  1400. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.281)
    1401. 

  1401. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1402. 

  1402. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.559
    1403. 

  1403. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1404. 

  1404. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1405. 

  1405. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1406. 

  1406. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.287)
    1407. 

  1407. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1408. 

  1408. 08/19/2021 10:46:56 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.558
    1409. 

  1409. 08/19/2021 10:46:56 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.559
    1410. 

  1410. 08/19/2021 10:46:56 AM - INFO - automl_search.py: 
    1411. 

  1411. Search finished after 05:14            
    1412. 

  1412. 08/19/2021 10:46:57 AM - INFO - automl_search.py: Best pipeline: LightGBM Classifier w/ Imputer
    1413. 

  1413. 08/19/2021 10:46:57 AM - INFO - automl_search.py: Best pipeline Log Loss Binary: 0.395200
    1414. 

  1414. 08/19/2021 10:46:58 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1415. 

  1415. 08/19/2021 10:46:58 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1416. 

  1416. 08/19/2021 10:46:59 AM - INFO - automl_search.py: Generating pipelines to search over...
    1417. 

  1417. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1418. 

  1418. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1419. 

  1419. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1420. 

  1420. 08/19/2021 10:46:59 AM - DEBUG - automl_search.py: allowed_estimators set to ['Decision Tree Classifier', 'LightGBM Classifier', 'Extra Trees Classifier', 'Elastic Net Classifier', 'CatBoost Classifier', 'XGBoost Classifier', 'Random Forest Classifier', 'Logistic Regression Classifier']
    1421. 

  1421. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1422. 

  1422. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1423. 

  1423. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1424. 

  1424. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1425. 

  1425. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1426. 

  1426. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1427. 

  1427. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1428. 

  1428. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1429. 

  1429. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1430. 

  1430. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1431. 

  1431. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1432. 

  1432. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1433. 

  1433. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1434. 

  1434. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1435. 

  1435. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1436. 

  1436. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1437. 

  1437. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1438. 

  1438. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1439. 

  1439. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1440. 

  1440. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1441. 

  1441. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1442. 

  1442. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1443. 

  1443. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1444. 

  1444. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1445. 

  1445. 08/19/2021 10:46:59 AM - INFO - automl_search.py: 8 pipelines ready for search.
    1446. 

  1446. 08/19/2021 10:46:59 AM - DEBUG - automl_search.py: allowed_pipelines set to ['Decision Tree Classifier w/ Imputer', 'LightGBM Classifier w/ Imputer', 'Extra Trees Classifier w/ Imputer', 'Elastic Net Classifier w/ Imputer + Standard Scaler', 'CatBoost Classifier w/ Imputer', 'XGBoost Classifier w/ Imputer', 'Random Forest Classifier w/ Imputer', 'Logistic Regression Classifier w/ Imputer + Standard Scaler']
    1447. 

  1447. 08/19/2021 10:46:59 AM - DEBUG - automl_search.py: allowed_model_families set to [ModelFamily.XGBOOST, ModelFamily.RANDOM_FOREST, ModelFamily.CATBOOST, ModelFamily.EXTRA_TREES, ModelFamily.LIGHTGBM, ModelFamily.DECISION_TREE, ModelFamily.LINEAR_MODEL]
    1448. 

  1448. 08/19/2021 10:46:59 AM - INFO - logger.py: 
    1449. 

  1449. *****************************
    1450. 

  1450. 08/19/2021 10:46:59 AM - INFO - logger.py: * Beginning pipeline search *
    1451. 

  1451. 08/19/2021 10:46:59 AM - INFO - logger.py: *****************************
    1452. 

  1452. 08/19/2021 10:46:59 AM - INFO - logger.py: 
    1453. 

  1453. 08/19/2021 10:46:59 AM - INFO - automl_search.py: Optimizing for Log Loss Binary. 
    1454. 

  1454. 08/19/2021 10:46:59 AM - INFO - automl_search.py: Lower score is better.
    1455. 

  1455. 

  1456. 08/19/2021 10:46:59 AM - INFO - automl_search.py: Using SequentialEngine to train and score pipelines.
    1457. 

  1457. 08/19/2021 10:46:59 AM - INFO - automl_search.py: Will stop searching for new pipelines after 300 seconds.
    1458. 

  1458. 

  1459. 08/19/2021 10:46:59 AM - INFO - automl_search.py: Allowed model families: xgboost, random_forest, catboost, extra_trees, lightgbm, decision_tree, linear_model
    1460. 

  1460. 

  1461. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1462. 

  1462. 08/19/2021 10:46:59 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1463. 

  1463. 08/19/2021 10:46:59 AM - INFO - automl_search.py: Evaluating Baseline Pipeline: Mode Baseline Binary Classification Pipeline
    1464. 

  1464. 08/19/2021 10:47:04 AM - INFO - engine_base.py: Mode Baseline Binary Classification Pipeline:
    1465. 

  1465. 08/19/2021 10:47:04 AM - INFO - engine_base.py: 	Starting cross validation
    1466. 

  1466. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1467. 

  1467. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1468. 

  1468. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1469. 

  1469. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.000)
    1470. 

  1470. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1471. 

  1471. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 9.375
    1472. 

  1472. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1473. 

  1473. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1474. 

  1474. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1475. 

  1475. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.000)
    1476. 

  1476. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1477. 

  1477. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 9.384
    1478. 

  1478. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1479. 

  1479. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1480. 

  1480. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1481. 

  1481. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.000)
    1482. 

  1482. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1483. 

  1483. 08/19/2021 10:47:04 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 9.384
    1484. 

  1484. 08/19/2021 10:47:04 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 9.381
    1485. 

  1485. 08/19/2021 10:47:04 AM - INFO - logger.py: 
    1486. 

  1486. *****************************
    1487. 

  1487. 08/19/2021 10:47:04 AM - INFO - logger.py: * Evaluating Batch Number 1 *
    1488. 

  1488. 08/19/2021 10:47:04 AM - INFO - logger.py: *****************************
    1489. 

  1489. 08/19/2021 10:47:04 AM - INFO - logger.py: 
    1490. 

  1490. 08/19/2021 10:47:11 AM - INFO - engine_base.py: Elastic Net Classifier w/ Imputer + Standard Scaler:
    1491. 

  1491. 08/19/2021 10:47:11 AM - INFO - engine_base.py: 	Starting cross validation
    1492. 

  1492. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1493. 

  1493. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1494. 

  1494. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1495. 

  1495. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.244)
    1496. 

  1496. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1497. 

  1497. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.560
    1498. 

  1498. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1499. 

  1499. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1500. 

  1500. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1501. 

  1501. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.218)
    1502. 

  1502. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1503. 

  1503. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.559
    1504. 

  1504. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1505. 

  1505. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1506. 

  1506. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1507. 

  1507. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.236)
    1508. 

  1508. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1509. 

  1509. 08/19/2021 10:47:11 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.556
    1510. 

  1510. 08/19/2021 10:47:11 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.558
    1511. 

  1511. 08/19/2021 10:47:19 AM - INFO - engine_base.py: Decision Tree Classifier w/ Imputer:
    1512. 

  1512. 08/19/2021 10:47:19 AM - INFO - engine_base.py: 	Starting cross validation
    1513. 

  1513. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1514. 

  1514. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1515. 

  1515. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1516. 

  1516. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (-0.000)
    1517. 

  1517. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1518. 

  1518. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.554
    1519. 

  1519. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1520. 

  1520. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1521. 

  1521. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1522. 

  1522. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.212)
    1523. 

  1523. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1524. 

  1524. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.642
    1525. 

  1525. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1526. 

  1526. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1527. 

  1527. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1528. 

  1528. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (-0.000)
    1529. 

  1529. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1530. 

  1530. 08/19/2021 10:47:19 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.560
    1531. 

  1531. 08/19/2021 10:47:19 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.585
    1532. 

  1532. 08/19/2021 10:47:30 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    1533. 

  1533. 08/19/2021 10:47:30 AM - INFO - engine_base.py: 	Starting cross validation
    1534. 

  1534. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1535. 

  1535. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1536. 

  1536. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1537. 

  1537. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.289)
    1538. 

  1538. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1539. 

  1539. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.457
    1540. 

  1540. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1541. 

  1541. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1542. 

  1542. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1543. 

  1543. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.318)
    1544. 

  1544. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1545. 

  1545. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.463
    1546. 

  1546. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1547. 

  1547. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1548. 

  1548. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1549. 

  1549. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.339)
    1550. 

  1550. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1551. 

  1551. 08/19/2021 10:47:30 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.462
    1552. 

  1552. 08/19/2021 10:47:30 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.460
    1553. 

  1553. 08/19/2021 10:47:41 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1554. 

  1554. 08/19/2021 10:47:41 AM - INFO - engine_base.py: 	Starting cross validation
    1555. 

  1555. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1556. 

  1556. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1557. 

  1557. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1558. 

  1558. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.340)
    1559. 

  1559. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1560. 

  1560. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.378
    1561. 

  1561. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1562. 

  1562. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1563. 

  1563. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1564. 

  1564. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.356)
    1565. 

  1565. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1566. 

  1566. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.392
    1567. 

  1567. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1568. 

  1568. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1569. 

  1569. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1570. 

  1570. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.362)
    1571. 

  1571. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1572. 

  1572. 08/19/2021 10:47:41 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.392
    1573. 

  1573. 08/19/2021 10:47:41 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.387
    1574. 

  1574. 08/19/2021 10:47:55 AM - INFO - engine_base.py: Logistic Regression Classifier w/ Imputer + Standard Scaler:
    1575. 

  1575. 08/19/2021 10:47:55 AM - INFO - engine_base.py: 	Starting cross validation
    1576. 

  1576. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1577. 

  1577. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1578. 

  1578. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1579. 

  1579. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.246)
    1580. 

  1580. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1581. 

  1581. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.560
    1582. 

  1582. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1583. 

  1583. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1584. 

  1584. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1585. 

  1585. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.216)
    1586. 

  1586. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1587. 

  1587. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.559
    1588. 

  1588. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1589. 

  1589. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1590. 

  1590. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1591. 

  1591. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.234)
    1592. 

  1592. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1593. 

  1593. 08/19/2021 10:47:55 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.556
    1594. 

  1594. 08/19/2021 10:47:55 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.558
    1595. 

  1595. 08/19/2021 10:49:10 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    1596. 

  1596. 08/19/2021 10:49:10 AM - INFO - engine_base.py: 	Starting cross validation
    1597. 

  1597. 08/19/2021 10:49:10 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1598. 

  1598. 08/19/2021 10:49:10 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1599. 

  1599. 08/19/2021 10:49:10 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1600. 

  1600. 08/19/2021 10:49:10 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.261)
    1601. 

  1601. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1602. 

  1602. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.382
    1603. 

  1603. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1604. 

  1604. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1605. 

  1605. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1606. 

  1606. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.318)
    1607. 

  1607. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1608. 

  1608. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.401
    1609. 

  1609. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1610. 

  1610. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1611. 

  1611. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1612. 

  1612. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.409)
    1613. 

  1613. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1614. 

  1614. 08/19/2021 10:49:11 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.398
    1615. 

  1615. 08/19/2021 10:49:11 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.394
    1616. 

  1616. 08/19/2021 10:49:22 AM - INFO - engine_base.py: Extra Trees Classifier w/ Imputer:
    1617. 

  1617. 08/19/2021 10:49:22 AM - INFO - engine_base.py: 	Starting cross validation
    1618. 

  1618. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1619. 

  1619. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1620. 

  1620. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1621. 

  1621. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.293)
    1622. 

  1622. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1623. 

  1623. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.540
    1624. 

  1624. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1625. 

  1625. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1626. 

  1626. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1627. 

  1627. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.287)
    1628. 

  1628. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1629. 

  1629. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.545
    1630. 

  1630. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1631. 

  1631. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1632. 

  1632. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1633. 

  1633. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.294)
    1634. 

  1634. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1635. 

  1635. 08/19/2021 10:49:22 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.542
    1636. 

  1636. 08/19/2021 10:49:22 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.542
    1637. 

  1637. 08/19/2021 10:49:26 AM - INFO - engine_base.py: CatBoost Classifier w/ Imputer:
    1638. 

  1638. 08/19/2021 10:49:26 AM - INFO - engine_base.py: 	Starting cross validation
    1639. 

  1639. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1640. 

  1640. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1641. 

  1641. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1642. 

  1642. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.434)
    1643. 

  1643. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1644. 

  1644. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.630
    1645. 

  1645. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1646. 

  1646. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1647. 

  1647. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1648. 

  1648. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.444)
    1649. 

  1649. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1650. 

  1650. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.631
    1651. 

  1651. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1652. 

  1652. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1653. 

  1653. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1654. 

  1654. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.434)
    1655. 

  1655. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1656. 

  1656. 08/19/2021 10:49:26 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.626
    1657. 

  1657. 08/19/2021 10:49:26 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.629
    1658. 

  1658. 08/19/2021 10:49:27 AM - INFO - logger.py: 
    1659. 

  1659. *****************************
    1660. 

  1660. 08/19/2021 10:49:27 AM - INFO - logger.py: * Evaluating Batch Number 2 *
    1661. 

  1661. 08/19/2021 10:49:27 AM - INFO - logger.py: *****************************
    1662. 

  1662. 08/19/2021 10:49:27 AM - INFO - logger.py: 
    1663. 

  1663. 08/19/2021 10:49:34 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1664. 

  1664. 08/19/2021 10:49:34 AM - INFO - engine_base.py: 	Starting cross validation
    1665. 

  1665. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1666. 

  1666. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1667. 

  1667. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1668. 

  1668. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.307)
    1669. 

  1669. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1670. 

  1670. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.485
    1671. 

  1671. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1672. 

  1672. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1673. 

  1673. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1674. 

  1674. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.325)
    1675. 

  1675. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1676. 

  1676. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.492
    1677. 

  1677. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1678. 

  1678. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1679. 

  1679. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1680. 

  1680. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.318)
    1681. 

  1681. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1682. 

  1682. 08/19/2021 10:49:34 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.487
    1683. 

  1683. 08/19/2021 10:49:34 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.488
    1684. 

  1684. 08/19/2021 10:49:42 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1685. 

  1685. 08/19/2021 10:49:42 AM - INFO - engine_base.py: 	Starting cross validation
    1686. 

  1686. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1687. 

  1687. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1688. 

  1688. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1689. 

  1689. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.293)
    1690. 

  1690. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1691. 

  1691. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.522
    1692. 

  1692. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1693. 

  1693. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1694. 

  1694. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1695. 

  1695. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.249)
    1696. 

  1696. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1697. 

  1697. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.520
    1698. 

  1698. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1699. 

  1699. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1700. 

  1700. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1701. 

  1701. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.252)
    1702. 

  1702. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1703. 

  1703. 08/19/2021 10:49:42 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.523
    1704. 

  1704. 08/19/2021 10:49:42 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.522
    1705. 

  1705. 08/19/2021 10:49:51 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1706. 

  1706. 08/19/2021 10:49:51 AM - INFO - engine_base.py: 	Starting cross validation
    1707. 

  1707. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1708. 

  1708. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1709. 

  1709. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1710. 

  1710. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.288)
    1711. 

  1711. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1712. 

  1712. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.491
    1713. 

  1713. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1714. 

  1714. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1715. 

  1715. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1716. 

  1716. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.290)
    1717. 

  1717. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1718. 

  1718. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.495
    1719. 

  1719. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1720. 

  1720. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1721. 

  1721. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1722. 

  1722. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.298)
    1723. 

  1723. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1724. 

  1724. 08/19/2021 10:49:51 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.493
    1725. 

  1725. 08/19/2021 10:49:51 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.493
    1726. 

  1726. 08/19/2021 10:50:04 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1727. 

  1727. 08/19/2021 10:50:04 AM - INFO - engine_base.py: 	Starting cross validation
    1728. 

  1728. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1729. 

  1729. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1730. 

  1730. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1731. 

  1731. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.350)
    1732. 

  1732. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1733. 

  1733. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.579
    1734. 

  1734. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1735. 

  1735. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1736. 

  1736. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1737. 

  1737. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.495)
    1738. 

  1738. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1739. 

  1739. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.612
    1740. 

  1740. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1741. 

  1741. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1742. 

  1742. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1743. 

  1743. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.218)
    1744. 

  1744. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1745. 

  1745. 08/19/2021 10:50:04 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.601
    1746. 

  1746. 08/19/2021 10:50:04 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.597
    1747. 

  1747. 08/19/2021 10:50:15 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    1748. 

  1748. 08/19/2021 10:50:15 AM - INFO - engine_base.py: 	Starting cross validation
    1749. 

  1749. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1750. 

  1750. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1751. 

  1751. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1752. 

  1752. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.223)
    1753. 

  1753. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1754. 

  1754. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.390
    1755. 

  1755. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1756. 

  1756. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1757. 

  1757. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1758. 

  1758. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.339)
    1759. 

  1759. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1760. 

  1760. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.413
    1761. 

  1761. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1762. 

  1762. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1763. 

  1763. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1764. 

  1764. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.323)
    1765. 

  1765. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1766. 

  1766. 08/19/2021 10:50:15 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.420
    1767. 

  1767. 08/19/2021 10:50:15 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.408
    1768. 

  1768. 08/19/2021 10:50:15 AM - INFO - logger.py: 
    1769. 

  1769. *****************************
    1770. 

  1770. 08/19/2021 10:50:15 AM - INFO - logger.py: * Evaluating Batch Number 3 *
    1771. 

  1771. 08/19/2021 10:50:15 AM - INFO - logger.py: *****************************
    1772. 

  1772. 08/19/2021 10:50:15 AM - INFO - logger.py: 
    1773. 

  1773. 08/19/2021 10:52:23 AM - INFO - engine_base.py: XGBoost Classifier w/ Imputer:
    1774. 

  1774. 08/19/2021 10:52:23 AM - INFO - engine_base.py: 	Starting cross validation
    1775. 

  1775. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1776. 

  1776. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1777. 

  1777. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1778. 

  1778. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.272)
    1779. 

  1779. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1780. 

  1780. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.583
    1781. 

  1781. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1782. 

  1782. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1783. 

  1783. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1784. 

  1784. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.146)
    1785. 

  1785. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1786. 

  1786. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.655
    1787. 

  1787. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1788. 

  1788. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1789. 

  1789. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1790. 

  1790. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.327)
    1791. 

  1791. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1792. 

  1792. 08/19/2021 10:52:23 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.641
    1793. 

  1793. 08/19/2021 10:52:23 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.626
    1794. 

  1794. 08/19/2021 10:52:23 AM - INFO - automl_search.py: 
    1795. 

  1795. Search finished after 05:23            
    1796. 

  1796. 08/19/2021 10:52:29 AM - INFO - automl_search.py: Best pipeline: LightGBM Classifier w/ Imputer
    1797. 

  1797. 08/19/2021 10:52:29 AM - INFO - automl_search.py: Best pipeline Log Loss Binary: 0.387466
    1798. 

  1798. 08/19/2021 10:52:33 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1799. 

  1799. 08/19/2021 10:52:33 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1800. 

  1800. 08/19/2021 11:32:45 AM - INFO - automl_search.py: Generating pipelines to search over...
    1801. 

  1801. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1802. 

  1802. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1803. 

  1803. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1804. 

  1804. 08/19/2021 11:32:48 AM - DEBUG - automl_search.py: allowed_estimators set to ['Decision Tree Classifier', 'LightGBM Classifier', 'Extra Trees Classifier', 'Elastic Net Classifier', 'CatBoost Classifier', 'XGBoost Classifier', 'Random Forest Classifier', 'Logistic Regression Classifier']
    1805. 

  1805. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1806. 

  1806. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1807. 

  1807. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1808. 

  1808. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1809. 

  1809. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1810. 

  1810. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1811. 

  1811. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1812. 

  1812. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1813. 

  1813. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1814. 

  1814. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1815. 

  1815. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1816. 

  1816. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1817. 

  1817. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1818. 

  1818. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1819. 

  1819. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1820. 

  1820. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1821. 

  1821. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1822. 

  1822. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1823. 

  1823. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1824. 

  1824. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1825. 

  1825. 08/19/2021 11:32:48 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1826. 

  1826. 08/19/2021 11:32:49 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1827. 

  1827. 08/19/2021 11:32:49 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1828. 

  1828. 08/19/2021 11:32:49 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1829. 

  1829. 08/19/2021 11:32:49 AM - INFO - automl_search.py: 8 pipelines ready for search.
    1830. 

  1830. 08/19/2021 11:32:49 AM - DEBUG - automl_search.py: allowed_pipelines set to ['Decision Tree Classifier w/ Imputer', 'LightGBM Classifier w/ Imputer', 'Extra Trees Classifier w/ Imputer', 'Elastic Net Classifier w/ Imputer + Standard Scaler', 'CatBoost Classifier w/ Imputer', 'XGBoost Classifier w/ Imputer', 'Random Forest Classifier w/ Imputer', 'Logistic Regression Classifier w/ Imputer + Standard Scaler']
    1831. 

  1831. 08/19/2021 11:32:49 AM - DEBUG - automl_search.py: allowed_model_families set to [ModelFamily.CATBOOST, ModelFamily.XGBOOST, ModelFamily.RANDOM_FOREST, ModelFamily.DECISION_TREE, ModelFamily.LIGHTGBM, ModelFamily.LINEAR_MODEL, ModelFamily.EXTRA_TREES]
    1832. 

  1832. 08/19/2021 11:32:49 AM - INFO - logger.py: 
    1833. 

  1833. *****************************
    1834. 

  1834. 08/19/2021 11:32:49 AM - INFO - logger.py: * Beginning pipeline search *
    1835. 

  1835. 08/19/2021 11:32:49 AM - INFO - logger.py: *****************************
    1836. 

  1836. 08/19/2021 11:32:49 AM - INFO - logger.py: 
    1837. 

  1837. 08/19/2021 11:32:49 AM - INFO - automl_search.py: Optimizing for Log Loss Binary. 
    1838. 

  1838. 08/19/2021 11:32:49 AM - INFO - automl_search.py: Lower score is better.
    1839. 

  1839. 

  1840. 08/19/2021 11:32:49 AM - INFO - automl_search.py: Using SequentialEngine to train and score pipelines.
    1841. 

  1841. 08/19/2021 11:32:49 AM - INFO - automl_search.py: Will stop searching for new pipelines after 300 seconds.
    1842. 

  1842. 

  1843. 08/19/2021 11:32:49 AM - INFO - automl_search.py: Allowed model families: catboost, xgboost, random_forest, decision_tree, lightgbm, linear_model, extra_trees
    1844. 

  1844. 

  1845. 08/19/2021 11:32:54 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1846. 

  1846. 08/19/2021 11:32:54 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1847. 

  1847. 08/19/2021 11:32:54 AM - INFO - automl_search.py: Evaluating Baseline Pipeline: Mode Baseline Binary Classification Pipeline
    1848. 

  1848. 08/19/2021 11:33:03 AM - INFO - engine_base.py: Mode Baseline Binary Classification Pipeline:
    1849. 

  1849. 08/19/2021 11:33:03 AM - INFO - engine_base.py: 	Starting cross validation
    1850. 

  1850. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1851. 

  1851. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1852. 

  1852. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1853. 

  1853. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.000)
    1854. 

  1854. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1855. 

  1855. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 9.393
    1856. 

  1856. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1857. 

  1857. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1858. 

  1858. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1859. 

  1859. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.000)
    1860. 

  1860. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1861. 

  1861. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 9.393
    1862. 

  1862. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1863. 

  1863. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1864. 

  1864. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1865. 

  1865. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.000)
    1866. 

  1866. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1867. 

  1867. 08/19/2021 11:33:03 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 9.401
    1868. 

  1868. 08/19/2021 11:33:03 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 9.396
    1869. 

  1869. 08/19/2021 11:33:04 AM - INFO - logger.py: 
    1870. 

  1870. *****************************
    1871. 

  1871. 08/19/2021 11:33:04 AM - INFO - logger.py: * Evaluating Batch Number 1 *
    1872. 

  1872. 08/19/2021 11:33:04 AM - INFO - logger.py: *****************************
    1873. 

  1873. 08/19/2021 11:33:04 AM - INFO - logger.py: 
    1874. 

  1874. 08/19/2021 11:33:20 AM - INFO - engine_base.py: Elastic Net Classifier w/ Imputer + Standard Scaler:
    1875. 

  1875. 08/19/2021 11:33:20 AM - INFO - engine_base.py: 	Starting cross validation
    1876. 

  1876. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1877. 

  1877. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1878. 

  1878. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1879. 

  1879. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.201)
    1880. 

  1880. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1881. 

  1881. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.562
    1882. 

  1882. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1883. 

  1883. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1884. 

  1884. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1885. 

  1885. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.240)
    1886. 

  1886. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1887. 

  1887. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.555
    1888. 

  1888. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1889. 

  1889. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1890. 

  1890. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1891. 

  1891. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.242)
    1892. 

  1892. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1893. 

  1893. 08/19/2021 11:33:20 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.559
    1894. 

  1894. 08/19/2021 11:33:20 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.559
    1895. 

  1895. 08/19/2021 11:33:27 AM - INFO - engine_base.py: Decision Tree Classifier w/ Imputer:
    1896. 

  1896. 08/19/2021 11:33:27 AM - INFO - engine_base.py: 	Starting cross validation
    1897. 

  1897. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1898. 

  1898. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1899. 

  1899. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1900. 

  1900. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.377)
    1901. 

  1901. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1902. 

  1902. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.637
    1903. 

  1903. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1904. 

  1904. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1905. 

  1905. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1906. 

  1906. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.250)
    1907. 

  1907. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1908. 

  1908. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.562
    1909. 

  1909. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1910. 

  1910. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1911. 

  1911. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1912. 

  1912. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (-0.000)
    1913. 

  1913. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1914. 

  1914. 08/19/2021 11:33:27 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.609
    1915. 

  1915. 08/19/2021 11:33:27 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.603
    1916. 

  1916. 08/19/2021 11:33:44 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    1917. 

  1917. 08/19/2021 11:33:44 AM - INFO - engine_base.py: 	Starting cross validation
    1918. 

  1918. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1919. 

  1919. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1920. 

  1920. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1921. 

  1921. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.344)
    1922. 

  1922. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1923. 

  1923. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.466
    1924. 

  1924. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1925. 

  1925. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1926. 

  1926. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1927. 

  1927. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.326)
    1928. 

  1928. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1929. 

  1929. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.466
    1930. 

  1930. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    1931. 

  1931. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    1932. 

  1932. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    1933. 

  1933. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.293)
    1934. 

  1934. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    1935. 

  1935. 08/19/2021 11:33:44 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.462
    1936. 

  1936. 08/19/2021 11:33:44 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.464
    1937. 

  1937. 08/19/2021 11:45:08 AM - INFO - automl_search.py: Generating pipelines to search over...
    1938. 

  1938. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1939. 

  1939. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1940. 

  1940. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1941. 

  1941. 08/19/2021 11:45:10 AM - DEBUG - automl_search.py: allowed_estimators set to ['Decision Tree Classifier', 'LightGBM Classifier', 'Extra Trees Classifier', 'Elastic Net Classifier', 'CatBoost Classifier', 'XGBoost Classifier', 'Random Forest Classifier', 'Logistic Regression Classifier']
    1942. 

  1942. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1943. 

  1943. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1944. 

  1944. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1945. 

  1945. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1946. 

  1946. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1947. 

  1947. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1948. 

  1948. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1949. 

  1949. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1950. 

  1950. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1951. 

  1951. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1952. 

  1952. 08/19/2021 11:45:10 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1953. 

  1953. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1954. 

  1954. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1955. 

  1955. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1956. 

  1956. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1957. 

  1957. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1958. 

  1958. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1959. 

  1959. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1960. 

  1960. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1961. 

  1961. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1962. 

  1962. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1963. 

  1963. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1964. 

  1964. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1965. 

  1965. 08/19/2021 11:45:11 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1966. 

  1966. 08/19/2021 11:45:11 AM - INFO - automl_search.py: 8 pipelines ready for search.
    1967. 

  1967. 08/19/2021 11:45:11 AM - DEBUG - automl_search.py: allowed_pipelines set to ['Decision Tree Classifier w/ Imputer', 'LightGBM Classifier w/ Imputer', 'Extra Trees Classifier w/ Imputer', 'Elastic Net Classifier w/ Imputer + Standard Scaler', 'CatBoost Classifier w/ Imputer', 'XGBoost Classifier w/ Imputer', 'Random Forest Classifier w/ Imputer', 'Logistic Regression Classifier w/ Imputer + Standard Scaler']
    1968. 

  1968. 08/19/2021 11:45:11 AM - DEBUG - automl_search.py: allowed_model_families set to [ModelFamily.EXTRA_TREES, ModelFamily.RANDOM_FOREST, ModelFamily.LINEAR_MODEL, ModelFamily.LIGHTGBM, ModelFamily.CATBOOST, ModelFamily.XGBOOST, ModelFamily.DECISION_TREE]
    1969. 

  1969. 08/19/2021 11:45:11 AM - INFO - logger.py: 
    1970. 

  1970. *****************************
    1971. 

  1971. 08/19/2021 11:45:11 AM - INFO - logger.py: * Beginning pipeline search *
    1972. 

  1972. 08/19/2021 11:45:11 AM - INFO - logger.py: *****************************
    1973. 

  1973. 08/19/2021 11:45:11 AM - INFO - logger.py: 
    1974. 

  1974. 08/19/2021 11:45:11 AM - INFO - automl_search.py: Optimizing for Log Loss Binary. 
    1975. 

  1975. 08/19/2021 11:45:11 AM - INFO - automl_search.py: Lower score is better.
    1976. 

  1976. 

  1977. 08/19/2021 11:45:11 AM - INFO - automl_search.py: Using SequentialEngine to train and score pipelines.
    1978. 

  1978. 08/19/2021 11:45:11 AM - INFO - automl_search.py: Will stop searching for new pipelines after 300 seconds.
    1979. 

  1979. 

  1980. 08/19/2021 11:45:11 AM - INFO - automl_search.py: Allowed model families: extra_trees, random_forest, linear_model, lightgbm, catboost, xgboost, decision_tree
    1981. 

  1981. 

  1982. 08/19/2021 11:45:13 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1983. 

  1983. 08/19/2021 11:45:13 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    1984. 

  1984. 08/19/2021 11:45:13 AM - INFO - automl_search.py: Evaluating Baseline Pipeline: Mode Baseline Binary Classification Pipeline
    1985. 

  1985. 08/19/2021 11:45:23 AM - INFO - engine_base.py: Mode Baseline Binary Classification Pipeline:
    1986. 

  1986. 08/19/2021 11:45:23 AM - INFO - engine_base.py: 	Starting cross validation
    1987. 

  1987. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    1988. 

  1988. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    1989. 

  1989. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    1990. 

  1990. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.000)
    1991. 

  1991. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    1992. 

  1992. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 9.254
    1993. 

  1993. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    1994. 

  1994. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    1995. 

  1995. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    1996. 

  1996. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.000)
    1997. 

  1997. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    1998. 

  1998. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 9.254
    1999. 

  1999. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2000. 

  2000. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    2001. 

  2001. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    2002. 

  2002. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.000)
    2003. 

  2003. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2004. 

  2004. 08/19/2021 11:45:23 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 9.254
    2005. 

  2005. 08/19/2021 11:45:23 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 9.254
    2006. 

  2006. 08/19/2021 11:45:23 AM - INFO - logger.py: 
    2007. 

  2007. *****************************
    2008. 

  2008. 08/19/2021 11:45:23 AM - INFO - logger.py: * Evaluating Batch Number 1 *
    2009. 

  2009. 08/19/2021 11:45:23 AM - INFO - logger.py: *****************************
    2010. 

  2010. 08/19/2021 11:45:23 AM - INFO - logger.py: 
    2011. 

  2011. 08/19/2021 11:45:34 AM - INFO - engine_base.py: Elastic Net Classifier w/ Imputer + Standard Scaler:
    2012. 

  2012. 08/19/2021 11:45:34 AM - INFO - engine_base.py: 	Starting cross validation
    2013. 

  2013. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    2014. 

  2014. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    2015. 

  2015. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    2016. 

  2016. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.202)
    2017. 

  2017. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    2018. 

  2018. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.557
    2019. 

  2019. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    2020. 

  2020. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    2021. 

  2021. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    2022. 

  2022. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.258)
    2023. 

  2023. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    2024. 

  2024. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.551
    2025. 

  2025. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2026. 

  2026. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    2027. 

  2027. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    2028. 

  2028. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.234)
    2029. 

  2029. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2030. 

  2030. 08/19/2021 11:45:34 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.554
    2031. 

  2031. 08/19/2021 11:45:34 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.554
    2032. 

  2032. 08/19/2021 11:45:42 AM - INFO - engine_base.py: Decision Tree Classifier w/ Imputer:
    2033. 

  2033. 08/19/2021 11:45:42 AM - INFO - engine_base.py: 	Starting cross validation
    2034. 

  2034. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    2035. 

  2035. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    2036. 

  2036. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    2037. 

  2037. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.267)
    2038. 

  2038. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    2039. 

  2039. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.601
    2040. 

  2040. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    2041. 

  2041. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    2042. 

  2042. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    2043. 

  2043. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.255)
    2044. 

  2044. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    2045. 

  2045. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.635
    2046. 

  2046. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2047. 

  2047. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    2048. 

  2048. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    2049. 

  2049. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (-0.000)
    2050. 

  2050. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2051. 

  2051. 08/19/2021 11:45:42 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.662
    2052. 

  2052. 08/19/2021 11:45:42 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.633
    2053. 

  2053. 08/19/2021 11:46:01 AM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    2054. 

  2054. 08/19/2021 11:46:01 AM - INFO - engine_base.py: 	Starting cross validation
    2055. 

  2055. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    2056. 

  2056. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    2057. 

  2057. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    2058. 

  2058. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.300)
    2059. 

  2059. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    2060. 

  2060. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.453
    2061. 

  2061. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    2062. 

  2062. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    2063. 

  2063. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    2064. 

  2064. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.305)
    2065. 

  2065. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    2066. 

  2066. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.457
    2067. 

  2067. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2068. 

  2068. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    2069. 

  2069. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    2070. 

  2070. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.300)
    2071. 

  2071. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2072. 

  2072. 08/19/2021 11:46:01 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.453
    2073. 

  2073. 08/19/2021 11:46:01 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.454
    2074. 

  2074. 08/19/2021 11:53:57 AM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    2075. 

  2075. 08/19/2021 11:53:57 AM - INFO - engine_base.py: 	Starting cross validation
    2076. 

  2076. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    2077. 

  2077. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 0: starting training
    2078. 

  2078. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 0: finished training
    2079. 

  2079. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.374)
    2080. 

  2080. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    2081. 

  2081. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.385
    2082. 

  2082. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    2083. 

  2083. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 1: starting training
    2084. 

  2084. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 1: finished training
    2085. 

  2085. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.318)
    2086. 

  2086. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    2087. 

  2087. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.384
    2088. 

  2088. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2089. 

  2089. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 2: starting training
    2090. 

  2090. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 2: finished training
    2091. 

  2091. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.346)
    2092. 

  2092. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2093. 

  2093. 08/19/2021 11:53:57 AM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.392
    2094. 

  2094. 08/19/2021 11:53:57 AM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.387
    2095. 

  2095. 08/19/2021 11:53:58 AM - INFO - automl_search.py: 
    2096. 

  2096. Search finished after 08:44            
    2097. 

  2097. 08/19/2021 11:56:38 AM - INFO - automl_search.py: Best pipeline: LightGBM Classifier w/ Imputer
    2098. 

  2098. 08/19/2021 11:56:38 AM - INFO - automl_search.py: Best pipeline Log Loss Binary: 0.386912
    2099. 

  2099. 08/19/2021 11:59:07 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2100. 

  2100. 08/19/2021 11:59:07 AM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2101. 

  2101. 08/19/2021 02:18:39 PM - INFO - automl_search.py: Generating pipelines to search over...
    2102. 

  2102. 08/19/2021 02:18:45 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2103. 

  2103. 08/19/2021 02:18:46 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2104. 

  2104. 08/19/2021 02:18:46 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2105. 

  2105. 08/19/2021 02:18:46 PM - DEBUG - automl_search.py: allowed_estimators set to ['Decision Tree Classifier', 'LightGBM Classifier', 'Extra Trees Classifier', 'Elastic Net Classifier', 'CatBoost Classifier', 'XGBoost Classifier', 'Random Forest Classifier', 'Logistic Regression Classifier']
    2106. 

  2106. 08/19/2021 02:18:46 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2107. 

  2107. 08/19/2021 02:18:46 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2108. 

  2108. 08/19/2021 02:18:46 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2109. 

  2109. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2110. 

  2110. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2111. 

  2111. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2112. 

  2112. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2113. 

  2113. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2114. 

  2114. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2115. 

  2115. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2116. 

  2116. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2117. 

  2117. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2118. 

  2118. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2119. 

  2119. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2120. 

  2120. 08/19/2021 02:18:47 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2121. 

  2121. 08/19/2021 02:18:48 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2122. 

  2122. 08/19/2021 02:18:48 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2123. 

  2123. 08/19/2021 02:18:48 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2124. 

  2124. 08/19/2021 02:18:48 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2125. 

  2125. 08/19/2021 02:18:48 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2126. 

  2126. 08/19/2021 02:18:48 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2127. 

  2127. 08/19/2021 02:18:48 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2128. 

  2128. 08/19/2021 02:18:48 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2129. 

  2129. 08/19/2021 02:18:48 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2130. 

  2130. 08/19/2021 02:18:48 PM - INFO - automl_search.py: 8 pipelines ready for search.
    2131. 

  2131. 08/19/2021 02:18:48 PM - DEBUG - automl_search.py: allowed_pipelines set to ['Decision Tree Classifier w/ Imputer', 'LightGBM Classifier w/ Imputer', 'Extra Trees Classifier w/ Imputer', 'Elastic Net Classifier w/ Imputer + Standard Scaler', 'CatBoost Classifier w/ Imputer', 'XGBoost Classifier w/ Imputer', 'Random Forest Classifier w/ Imputer', 'Logistic Regression Classifier w/ Imputer + Standard Scaler']
    2132. 

  2132. 08/19/2021 02:18:48 PM - DEBUG - automl_search.py: allowed_model_families set to [ModelFamily.LINEAR_MODEL, ModelFamily.CATBOOST, ModelFamily.LIGHTGBM, ModelFamily.DECISION_TREE, ModelFamily.RANDOM_FOREST, ModelFamily.XGBOOST, ModelFamily.EXTRA_TREES]
    2133. 

  2133. 08/19/2021 02:18:50 PM - INFO - logger.py: 
    2134. 

  2134. *****************************
    2135. 

  2135. 08/19/2021 02:18:50 PM - INFO - logger.py: * Beginning pipeline search *
    2136. 

  2136. 08/19/2021 02:18:50 PM - INFO - logger.py: *****************************
    2137. 

  2137. 08/19/2021 02:18:50 PM - INFO - logger.py: 
    2138. 

  2138. 08/19/2021 02:18:50 PM - INFO - automl_search.py: Optimizing for Log Loss Binary. 
    2139. 

  2139. 08/19/2021 02:18:50 PM - INFO - automl_search.py: Lower score is better.
    2140. 

  2140. 

  2141. 08/19/2021 02:18:50 PM - INFO - automl_search.py: Using SequentialEngine to train and score pipelines.
    2142. 

  2142. 08/19/2021 02:18:50 PM - INFO - automl_search.py: Will stop searching for new pipelines after 300 seconds.
    2143. 

  2143. 

  2144. 08/19/2021 02:18:50 PM - INFO - automl_search.py: Allowed model families: linear_model, catboost, lightgbm, decision_tree, random_forest, xgboost, extra_trees
    2145. 

  2145. 

  2146. 08/19/2021 02:18:58 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2147. 

  2147. 08/19/2021 02:19:00 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2148. 

  2148. 08/19/2021 02:19:00 PM - INFO - automl_search.py: Evaluating Baseline Pipeline: Mode Baseline Binary Classification Pipeline
    2149. 

  2149. 08/19/2021 02:19:19 PM - INFO - engine_base.py: Mode Baseline Binary Classification Pipeline:
    2150. 

  2150. 08/19/2021 02:19:19 PM - INFO - engine_base.py: 	Starting cross validation
    2151. 

  2151. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    2152. 

  2152. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 0: starting training
    2153. 

  2153. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 0: finished training
    2154. 

  2154. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.000)
    2155. 

  2155. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    2156. 

  2156. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 9.193
    2157. 

  2157. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    2158. 

  2158. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 1: starting training
    2159. 

  2159. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 1: finished training
    2160. 

  2160. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.000)
    2161. 

  2161. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    2162. 

  2162. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 9.184
    2163. 

  2163. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2164. 

  2164. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 2: starting training
    2165. 

  2165. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 2: finished training
    2166. 

  2166. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.000)
    2167. 

  2167. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2168. 

  2168. 08/19/2021 02:19:19 PM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 9.184
    2169. 

  2169. 08/19/2021 02:19:19 PM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 9.187
    2170. 

  2170. 08/19/2021 02:19:19 PM - INFO - logger.py: 
    2171. 

  2171. *****************************
    2172. 

  2172. 08/19/2021 02:19:19 PM - INFO - logger.py: * Evaluating Batch Number 1 *
    2173. 

  2173. 08/19/2021 02:19:19 PM - INFO - logger.py: *****************************
    2174. 

  2174. 08/19/2021 02:19:19 PM - INFO - logger.py: 
    2175. 

  2175. 08/19/2021 02:19:41 PM - INFO - engine_base.py: Elastic Net Classifier w/ Imputer + Standard Scaler:
    2176. 

  2176. 08/19/2021 02:19:41 PM - INFO - engine_base.py: 	Starting cross validation
    2177. 

  2177. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    2178. 

  2178. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 0: starting training
    2179. 

  2179. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 0: finished training
    2180. 

  2180. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.246)
    2181. 

  2181. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    2182. 

  2182. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.552
    2183. 

  2183. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    2184. 

  2184. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 1: starting training
    2185. 

  2185. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 1: finished training
    2186. 

  2186. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.229)
    2187. 

  2187. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    2188. 

  2188. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.549
    2189. 

  2189. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2190. 

  2190. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 2: starting training
    2191. 

  2191. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 2: finished training
    2192. 

  2192. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.236)
    2193. 

  2193. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2194. 

  2194. 08/19/2021 02:19:41 PM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.555
    2195. 

  2195. 08/19/2021 02:19:41 PM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.552
    2196. 

  2196. 08/19/2021 02:20:01 PM - INFO - engine_base.py: Decision Tree Classifier w/ Imputer:
    2197. 

  2197. 08/19/2021 02:20:01 PM - INFO - engine_base.py: 	Starting cross validation
    2198. 

  2198. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    2199. 

  2199. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 0: starting training
    2200. 

  2200. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 0: finished training
    2201. 

  2201. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.455)
    2202. 

  2202. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    2203. 

  2203. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.632
    2204. 

  2204. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    2205. 

  2205. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 1: starting training
    2206. 

  2206. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 1: finished training
    2207. 

  2207. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.370)
    2208. 

  2208. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    2209. 

  2209. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.551
    2210. 

  2210. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2211. 

  2211. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 2: starting training
    2212. 

  2212. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 2: finished training
    2213. 

  2213. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.310)
    2214. 

  2214. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2215. 

  2215. 08/19/2021 02:20:01 PM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.561
    2216. 

  2216. 08/19/2021 02:20:01 PM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.581
    2217. 

  2217. 08/19/2021 02:20:33 PM - INFO - engine_base.py: Random Forest Classifier w/ Imputer:
    2218. 

  2218. 08/19/2021 02:20:33 PM - INFO - engine_base.py: 	Starting cross validation
    2219. 

  2219. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    2220. 

  2220. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 0: starting training
    2221. 

  2221. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 0: finished training
    2222. 

  2222. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.339)
    2223. 

  2223. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    2224. 

  2224. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.451
    2225. 

  2225. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    2226. 

  2226. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 1: starting training
    2227. 

  2227. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 1: finished training
    2228. 

  2228. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.307)
    2229. 

  2229. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    2230. 

  2230. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.456
    2231. 

  2231. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2232. 

  2232. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 2: starting training
    2233. 

  2233. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 2: finished training
    2234. 

  2234. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.326)
    2235. 

  2235. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2236. 

  2236. 08/19/2021 02:20:33 PM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.468
    2237. 

  2237. 08/19/2021 02:20:33 PM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.458
    2238. 

  2238. 08/19/2021 02:30:15 PM - INFO - engine_base.py: LightGBM Classifier w/ Imputer:
    2239. 

  2239. 08/19/2021 02:30:15 PM - INFO - engine_base.py: 	Starting cross validation
    2240. 

  2240. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 		Training and scoring on fold 0
    2241. 

  2241. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 0: starting training
    2242. 

  2242. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 0: finished training
    2243. 

  2243. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 0: Optimal threshold found (0.275)
    2244. 

  2244. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 0: Scoring trained pipeline
    2245. 

  2245. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 0: Log Loss Binary score: 0.373
    2246. 

  2246. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 		Training and scoring on fold 1
    2247. 

  2247. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 1: starting training
    2248. 

  2248. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 1: finished training
    2249. 

  2249. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 1: Optimal threshold found (0.378)
    2250. 

  2250. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 1: Scoring trained pipeline
    2251. 

  2251. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 1: Log Loss Binary score: 0.389
    2252. 

  2252. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 		Training and scoring on fold 2
    2253. 

  2253. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 2: starting training
    2254. 

  2254. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 2: finished training
    2255. 

  2255. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 2: Optimal threshold found (0.349)
    2256. 

  2256. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 2: Scoring trained pipeline
    2257. 

  2257. 08/19/2021 02:30:15 PM - DEBUG - engine_base.py: 			Fold 2: Log Loss Binary score: 0.408
    2258. 

  2258. 08/19/2021 02:30:15 PM - INFO - engine_base.py: 	Finished cross validation - mean Log Loss Binary: 0.390
    2259. 

  2259. 08/19/2021 02:30:15 PM - INFO - automl_search.py: 
    2260. 

  2260. Search finished after 11:17            
    2261. 

  2261. 08/19/2021 02:33:28 PM - INFO - automl_search.py: Best pipeline: LightGBM Classifier w/ Imputer
    2262. 

  2262. 08/19/2021 02:33:28 PM - INFO - automl_search.py: Best pipeline Log Loss Binary: 0.390168
    2263. 

  2263. 08/19/2021 02:36:32 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2264. 

  2264. 08/19/2021 02:36:32 PM - DEBUG - gen_utils.py: Could not import class ProphetRegressor in get_importable_subclasses
    2265.
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Integrate Google Cloud Storage
Use Google Storage
Select bucket
Upload key
Finish

Use Google Cloud Storage!

Browsing data directories saved to Google Cloud Storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your Google Storage bucket

Service Account Key

Congratulations!

Covid19-Vaccine-ML-Pipeline is now integrated with Google Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate AWS S3
Use S3 remote
Select bucket
Access key
Finish

Use AWS S3 as storage!

Browsing data directories saved to S3 is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your S3 bucket

Access key (If needed)

Congratulations!

Covid19-Vaccine-ML-Pipeline is now integrated with AWS S3!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate S3 compatible storage
Use S3 like remote
Select bucket
Access key
Finish

Use any S3 compatible storage!

Browsing data directories saved to S3 compatible storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your S3 bucket

Access key (If needed)

Congratulations!

Covid19-Vaccine-ML-Pipeline is now integrated with your S3 compatible storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate Azure Cloud Storage
Use Azure Storage
Select bucket
Set key
Finish

Use Azure Cloud Storage!

Browsing data directories saved to Azure Cloud Storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your Azure Storage bucket

Access key (If needed)

Congratulations!

Covid19-Vaccine-ML-Pipeline is now integrated with Azure Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes