Run
9353314

Run 9353314

Task 2079 (Supervised Classification) eucalyptus Uploaded 10-10-2018 by Jan van Rijn
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=s klearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imp uter,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=skle arn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotenco der=sklearn.preprocessing._encoders.OneHotEncoder)),adaboostclassifier=skle arn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree .tree.DecisionTreeClassifier))(1)Automatically created scikit-learn flow.
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_n_jobsnull
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_remainder"passthrough"
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_sparse_threshold0.3
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_transformer_weightsnull
sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
sklearn.impute.MissingIndicator(1)_error_on_newfalse
sklearn.impute.MissingIndicator(1)_features"missing-only"
sklearn.impute.MissingIndicator(1)_missing_valuesNaN
sklearn.impute.MissingIndicator(1)_sparse"auto"
sklearn.preprocessing.imputation.Imputer(29)_axis0
sklearn.preprocessing.imputation.Imputer(29)_copytrue
sklearn.preprocessing.imputation.Imputer(29)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(29)_strategy"mean"
sklearn.preprocessing.imputation.Imputer(29)_verbose0
sklearn.preprocessing.data.StandardScaler(14)_copytrue
sklearn.preprocessing.data.StandardScaler(14)_with_meantrue
sklearn.preprocessing.data.StandardScaler(14)_with_stdtrue
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memorynull
sklearn.impute.SimpleImputer(1)_copytrue
sklearn.impute.SimpleImputer(1)_fill_value-1
sklearn.impute.SimpleImputer(1)_missing_valuesNaN
sklearn.impute.SimpleImputer(1)_strategy"constant"
sklearn.impute.SimpleImputer(1)_verbose0
sklearn.preprocessing._encoders.OneHotEncoder(3)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_categoriesnull
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)_sparsetrue
sklearn.tree.tree.DecisionTreeClassifier(29)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(29)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(29)_max_depth4
sklearn.tree.tree.DecisionTreeClassifier(29)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(29)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(29)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(29)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(29)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(29)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(29)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(29)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(29)_random_state2499
sklearn.tree.tree.DecisionTreeClassifier(29)_splitter"best"
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),adaboostclassifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier))(1)_memorynull
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(8)_algorithm"SAMME"
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(8)_learning_rate0.35388587560272455
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(8)_n_estimators444
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(8)_random_state19094

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

0.7532 ± 0.0223
Per class
Cross-validation details (10-fold Crossvalidation)
0.4369 ± 0.0416
Per class
Cross-validation details (10-fold Crossvalidation)
0.2743 ± 0.0478
Cross-validation details (10-fold Crossvalidation)
32.8866 ± 0.114
Cross-validation details (10-fold Crossvalidation)
0.3194 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.3132 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
736
Per class
Cross-validation details (10-fold Crossvalidation)
0.4429 ± 0.0464
Per class
Cross-validation details (10-fold Crossvalidation)
0.4334 ± 0.0385
Cross-validation details (10-fold Crossvalidation)
2.2629
Cross-validation details (10-fold Crossvalidation)
0.4334 ± 0.0385
Per class
Cross-validation details (10-fold Crossvalidation)
1.0196 ± 0.001
Cross-validation details (10-fold Crossvalidation)
0.3957 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.3992 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
1.0088 ± 0.001
Cross-validation details (10-fold Crossvalidation)