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Task 9955 (Supervised Classification) one-hundred-plants-shape Uploaded 08-01-2019 by Scikit-learn Bot
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.pr eprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.St andardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.imput e.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder )),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceT hreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.Grad ientBoostingClassifier)(3)	Automatically created scikit-learn flow.
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(3)_memory	null
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_n_jobs	null
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_remainder	"passthrough"
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_sparse_threshold	0.3
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_transformer_weights	null
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(3)_memory	null
sklearn.preprocessing.imputation.Imputer(34)_axis	0
sklearn.preprocessing.imputation.Imputer(34)_copy	true
sklearn.preprocessing.imputation.Imputer(34)_missing_values	"NaN"
sklearn.preprocessing.imputation.Imputer(34)_strategy	"most_frequent"
sklearn.preprocessing.imputation.Imputer(34)_verbose	0
sklearn.preprocessing.data.StandardScaler(20)_copy	true
sklearn.preprocessing.data.StandardScaler(20)_with_mean	true
sklearn.preprocessing.data.StandardScaler(20)_with_std	true
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(3)_memory	null
sklearn.impute.SimpleImputer(6)_copy	true
sklearn.impute.SimpleImputer(6)_fill_value	-1
sklearn.impute.SimpleImputer(6)_missing_values	NaN
sklearn.impute.SimpleImputer(6)_strategy	"constant"
sklearn.impute.SimpleImputer(6)_verbose	0
sklearn.preprocessing._encoders.OneHotEncoder(6)_categorical_features	null
sklearn.preprocessing._encoders.OneHotEncoder(6)_categories	null
sklearn.preprocessing._encoders.OneHotEncoder(6)_dtype	{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(6)_handle_unknown	"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(6)_n_values	null
sklearn.preprocessing._encoders.OneHotEncoder(6)_sparse	true
sklearn.feature_selection.variance_threshold.VarianceThreshold(21)_threshold	0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_criterion	"friedman_mse"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_init	null
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_learning_rate	0.2938244765438634
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_loss	"deviance"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_max_depth	5
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_max_features	0.42541283804624475
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_max_leaf_nodes	null
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_min_impurity_decrease	0.8409464851191324
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_min_impurity_split	null
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_min_samples_leaf	11
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_min_samples_split	13
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_min_weight_fraction_leaf	0.3680806240244247
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_n_estimators	154
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_n_iter_no_change	17
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_presort	"auto"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_random_state	12443
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_subsample	0.384806463814363
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_tol	0.0015906074825183596
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_validation_fraction	0.21967356033926766
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_verbose	0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(16)_warm_start	false