Run
8784091

Run 8784091

Task 14965 (Supervised Classification) bank-marketing Uploaded 10-01-2018 by Vishal Chouskey
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  • openml-pimp openml-python Sklearn_0.18.2.
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.ensemble.forest.RandomForestClassifier)(4)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(14)_categorical_features[1, 2, 3, 4, 6, 7, 8, 10, 15]
sklearn.preprocessing.data.OneHotEncoder(14)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(14)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(14)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(14)_sparsetrue
sklearn.ensemble.forest.RandomForestClassifier(29)_bootstrapfalse
sklearn.ensemble.forest.RandomForestClassifier(29)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(29)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(29)_max_features0.19565815571418466
sklearn.ensemble.forest.RandomForestClassifier(29)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(29)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_leaf10
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_split3
sklearn.ensemble.forest.RandomForestClassifier(29)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(29)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(29)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(29)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(29)_random_state11662
sklearn.ensemble.forest.RandomForestClassifier(29)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(29)_warm_startfalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(9)_threshold0.0
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[1, 2, 3, 4, 6, 7, 8, 10, 15]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0

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

0.9271 ± 0.0073
Per class
Cross-validation details (10-fold Crossvalidation)
0.8944 ± 0.0051
Per class
Cross-validation details (10-fold Crossvalidation)
0.4473 ± 0.0286
Cross-validation details (10-fold Crossvalidation)
8969.8099 ± 106.7175
Cross-validation details (10-fold Crossvalidation)
0.1315 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
0.2066 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
45211
Per class
Cross-validation details (10-fold Crossvalidation)
0.892 ± 0.0057
Per class
Cross-validation details (10-fold Crossvalidation)
0.9042 ± 0.0042
Cross-validation details (10-fold Crossvalidation)
0.5207
Cross-validation details (10-fold Crossvalidation)
0.9042 ± 0.0042
Per class
Cross-validation details (10-fold Crossvalidation)
0.6367 ± 0.0129
Cross-validation details (10-fold Crossvalidation)
0.3214 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2536 ± 0.0046
Cross-validation details (10-fold Crossvalidation)
0.7891 ± 0.0144
Cross-validation details (10-fold Crossvalidation)