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graph_v3.1.txt 3.3 KB

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  1. {
  2. "imports": ["import", "from"],
  3. "data_load": [".load", "_load", "_dump", "load_", ".csv", "glob", "pickle.", "read_", "download", ".txt", ".json", ".png", ".jpg", ".jpeg"],
  4. "preprocessing": ["train_test_split(", "Normalizer(", "StandardScaler(", "normalize(", "scale(", "DictVectorizer(",
  5. "CountVectorizer(", "HashingVectorizer(", "TfidfVectorizer(", "Stemmer(",
  6. "Lemmatizer(", "convert", ".resize", "encode(", ".fill(", ".fillna(",
  7. ".concat(", ".concat (", ".concatenate(", ".concatenate (", "merge",
  8. "train_test_split (", "Normalizer (", "StandardScaler (", "normalize (",
  9. "scale (","DictVectorizer (", "CountVectorizer (", "HashingVectorizer (",
  10. "TfidfVectorizer (", "Stemmer (", "Lemmatizer (", "encode (", ".fill (",
  11. ".fillna (", "preprocess", "generation", "augmentation", "stemming",
  12. "lemmatization", "scale", ".normalize", ".crop", "crop(", "crop (", "resize(",
  13. "resize (", "invert_xaxis", "print_results", "attention", ".drop(", ".drop (",
  14. "preprocessing", "test_size", "test_split", "font_scale", "scale", "color_contonuous_scale",
  15. "colorscale", "encode", "preprocessor", "set_vscale", "rescale", "reversescale",
  16. "inverse_transform", "porterstemmer", "stem", "simple_preprocess",
  17. "ploynomialfeatures", "autoscale", "lemmatize", "lemmatizer", "pd_merge_all",
  18. "stemmer", "labelencoder", "LabelEncoder", "minmaxscaler", "converted",
  19. "preprocess_image", "vectorizer", "tokenizer", "tfidf", "stemmer", "scaled_train",
  20. "input_ids", "combined_merged", "pucountry_convert", "stemming", "replace", "lambda",
  21. "map(", "filter(", ".get_dummies", ".fit_transform", ".transform", ".strip", ".split",
  22. ".apply", ".dropna", "clean", "duplicated", "drop_duplicated", "decode", "reshape",
  23. "deskew", ".str.contains", "iaa.", "augmentation", "A.", "flatten", ".groupby",
  24. ".sort_values", ".pad", "prepare", "pivot", ".melt", "rotate", "re.", "sorted(",
  25. ".reset_index("
  26. ],
  27. "visualization": ["plotting", "plot.", "plt.", "graph", "histogram", "hist", "sns.", "plotline", "chart", "diagram", "heatmap", "figure", "plot_tree(", "plot_tree (", "boxplot"],
  28. "model": ["LinearRegression(", "RandomForest(", "Ridge(", "RidgeCV(", "RidgeClassifier(", "RidgeClassifierCV(", "Lasso(", "SGD(", "LogisticRegression(", "LogisticRegressionCV(", "SVC(", "SVR(",
  29. "Layer(", "XGboost(", "LGBM(", "CatBoost(", "Perceptron(", "KNeighborsRegressor(", "KNeighborsClassifier(", "SGDRegressor(", "ElasticNet(", "ElasticNetCV(", "KMeans(",
  30. "AgglomerativeClustering(", "SpectralClustering(", "CategoricalNB(", "ComplementNB(", "DecisionTreeClassifier(", "DecisionTreeRegressor(", "LinearRegression (", "RandomForest (",
  31. "Ridge (", "RidgeCV (", "RidgeClassifier (", "RidgeClassifierCV (", "Lasso (", "SGD (", "LogisticRegression (", "LogisticRegressionCV (", "SVC (", "SVR (", "Layer (", "XGboost (",
  32. "LGBM (", "CatBoost (", "Perceptron (", "KNeighborsRegressor (", "KNeighborsClassifier (", "SGDRegressor (", "ElasticNet (", "ElasticNetCV (", "KMeans (", "AgglomerativeClustering (",
  33. "SpectralClustering (", "CategoricalNB (", "ComplementNB (", "DecisionTreeClassifier (", "DecisionTreeRegressor ("],
  34. "train": [".fit", "epoch", "loss", "optimizer"],
  35. "predict": [".predict", "_error", ".mean_", "_score", "_distance"]
  36. }
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