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Run 3407

Task 1 (Supervised Classification) anneal Uploaded 04-11-2019 by Test Test
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Flow

sklearn.pipeline.Pipeline(Preprocessing=sklearn.compose._column_transformer .ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute ._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder) ),Classifier=sklearn.ensemble.forest.RandomForestClassifier)(3)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(7)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(7)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(7)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(7)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(7)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(7)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(7)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(7)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(7)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(7)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(7)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(7)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(7)_n_jobsnull
sklearn.ensemble.forest.RandomForestClassifier(7)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(7)_random_state43630
sklearn.ensemble.forest.RandomForestClassifier(7)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(7)_warm_startfalse
sklearn.impute._base.SimpleImputer(4)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(4)_copytrue
sklearn.impute._base.SimpleImputer(4)_fill_valuenull
sklearn.impute._base.SimpleImputer(4)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(4)_strategy"most_frequent"
sklearn.impute._base.SimpleImputer(4)_verbose0
sklearn.pipeline.Pipeline(Preprocessing=sklearn.compose._column_transformer.ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder)),Classifier=sklearn.ensemble.forest.RandomForestClassifier)(3)_memorynull
sklearn.pipeline.Pipeline(Preprocessing=sklearn.compose._column_transformer.ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder)),Classifier=sklearn.ensemble.forest.RandomForestClassifier)(3)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "Preprocessing", "step_name": "Preprocessing"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "Classifier", "step_name": "Classifier"}}]
sklearn.pipeline.Pipeline(Preprocessing=sklearn.compose._column_transformer.ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder)),Classifier=sklearn.ensemble.forest.RandomForestClassifier)(3)_verbosefalse
sklearn.compose._column_transformer.ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_n_jobsnull
sklearn.compose._column_transformer.ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_remainder"drop"
sklearn.compose._column_transformer.ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_sparse_threshold0.3
sklearn.compose._column_transformer.ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_transformer_weightsnull
sklearn.compose._column_transformer.ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "Nominal", "step_name": "Nominal", "argument_1": [0, 1, 2, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 35, 36, 37]}}]
sklearn.compose._column_transformer.ColumnTransformer(Nominal=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder))(3)_verbosefalse
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder)(3)_memorynull
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder)(3)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "Encoder", "step_name": "Encoder"}}]
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,Encoder=sklearn.preprocessing._encoders.OneHotEncoder)(3)_verbosefalse
sklearn.preprocessing._encoders.OneHotEncoder(3)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_dropnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(3)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(3)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsefalse

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

0.8895 ± 0.0231
Per class
Cross-validation details (10-fold Crossvalidation)
0.8388 ± 0.0285
Per class
Cross-validation details (10-fold Crossvalidation)
0.6023 ± 0.0681
Cross-validation details (10-fold Crossvalidation)
0.5491 ± 0.057
Cross-validation details (10-fold Crossvalidation)
0.0744 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
0.1343 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
0.8508 ± 0.0289
Cross-validation details (10-fold Crossvalidation)
898
Per class
Cross-validation details (10-fold Crossvalidation)
0.8428 ± 0.0369
Per class
Cross-validation details (10-fold Crossvalidation)
0.8508 ± 0.0289
Cross-validation details (10-fold Crossvalidation)
1.1915 ± 0.0248
Cross-validation details (10-fold Crossvalidation)
0.5539 ± 0.051
Cross-validation details (10-fold Crossvalidation)
0.2582 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
0.1949 ± 0.0115
Cross-validation details (10-fold Crossvalidation)
0.7548 ± 0.0416
Cross-validation details (10-fold Crossvalidation)