Run
6095160

Run 6095160

Task 4 (Supervised Classification) labor Uploaded 12-08-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1.
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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)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(21)_bootstrapfalse
sklearn.ensemble.forest.RandomForestClassifier(21)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(21)_criterion"entropy"
sklearn.ensemble.forest.RandomForestClassifier(21)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(21)_max_features0.18046851626378874
sklearn.ensemble.forest.RandomForestClassifier(21)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(21)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_leaf5
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_split6
sklearn.ensemble.forest.RandomForestClassifier(21)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(21)_n_estimators100
sklearn.ensemble.forest.RandomForestClassifier(21)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(21)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(21)_random_state58597
sklearn.ensemble.forest.RandomForestClassifier(21)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(21)_warm_startfalse
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[4, 6, 9, 11, 12, 13, 14, 15]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[4, 6, 9, 11, 12, 13, 14, 15]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0

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

0.9811 ± 0.0395
Per class
Cross-validation details (10-fold Crossvalidation)
0.9298 ± 0.095
Per class
Cross-validation details (10-fold Crossvalidation)
0.8459 ± 0.205
Cross-validation details (10-fold Crossvalidation)
33.0934 ± 0.968
Cross-validation details (10-fold Crossvalidation)
0.214 ± 0.0697
Cross-validation details (10-fold Crossvalidation)
0.457 ± 0.0093
Cross-validation details (10-fold Crossvalidation)
57
Per class
Cross-validation details (10-fold Crossvalidation)
0.9298 ± 0.0663
Per class
Cross-validation details (10-fold Crossvalidation)
0.9298 ± 0.0909
Cross-validation details (10-fold Crossvalidation)
0.9393
Cross-validation details (10-fold Crossvalidation)
0.9298 ± 0.0909
Per class
Cross-validation details (10-fold Crossvalidation)
0.4683 ± 0.1516
Cross-validation details (10-fold Crossvalidation)
0.4773 ± 0.0096
Cross-validation details (10-fold Crossvalidation)
0.27 ± 0.0886
Cross-validation details (10-fold Crossvalidation)
0.5657 ± 0.1851
Cross-validation details (10-fold Crossvalidation)