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Jeongrim Kim
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Jeongrim's flows

sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(transform=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.preprocessing._encoders.OneHotEncoder,cont=sklearn.impute._base.SimpleImputer),rf=sklearn.ensemble._forest.RandomForestClassifier)) (1)
Randomized search on hyper parameters. RandomizedSearchCV implements a "fit" and a "score" method. It also implements "score_samples", "predict", "predict_proba", "decision_function", "transform" and…
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sklearn.pipeline.Pipeline(transform=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.preprocessing._encoders.OneHotEncoder,cont=sklearn.impute._base.SimpleImputer),rf=sklearn.ensemble._forest.RandomForestClassifier) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.preprocessing._encoders.OneHotEncoder,cont=sklearn.impute._base.SimpleImputer) (1)
Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
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