Run
5873391

Run 5873391

Task 9950 (Supervised Classification) micro-mass Uploaded 13-07-2017 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_features0.3090888310013613
sklearn.ensemble.forest.RandomForestClassifier(21)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(21)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_leaf6
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_split15
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_state28952
sklearn.ensemble.forest.RandomForestClassifier(21)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(21)_warm_startfalse
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[]
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[]
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)_sparsefalse
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

0.9934 ± 0.0041
Per class
Cross-validation details (10-fold Crossvalidation)
0.8906 ± 0.0387
Per class
Cross-validation details (10-fold Crossvalidation)
0.8844 ± 0.0529
Cross-validation details (10-fold Crossvalidation)
476.095 ± 1.6886
Cross-validation details (10-fold Crossvalidation)
0.0305 ± 0.0038
Cross-validation details (10-fold Crossvalidation)
0.0941 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
571
Per class
Cross-validation details (10-fold Crossvalidation)
0.8973 ± 0.0273
Per class
Cross-validation details (10-fold Crossvalidation)
0.8914 ± 0.0496
Cross-validation details (10-fold Crossvalidation)
4.208
Cross-validation details (10-fold Crossvalidation)
0.8914 ± 0.0496
Per class
Cross-validation details (10-fold Crossvalidation)
0.3238 ± 0.0401
Cross-validation details (10-fold Crossvalidation)
0.2169 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.1038 ± 0.0119
Cross-validation details (10-fold Crossvalidation)
0.4787 ± 0.055
Cross-validation details (10-fold Crossvalidation)