Run
5814314

Run 5814314

Task 2079 (Supervised Classification) eucalyptus 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"gini"
sklearn.ensemble.forest.RandomForestClassifier(21)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(21)_max_features0.3747850047615564
sklearn.ensemble.forest.RandomForestClassifier(21)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(21)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_leaf10
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_split13
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_state28647
sklearn.ensemble.forest.RandomForestClassifier(21)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(21)_warm_startfalse
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[0, 2, 3, 4, 9]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[0, 2, 3, 4, 9]
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

0.9075 ± 0.0171
Per class
Cross-validation details (10-fold Crossvalidation)
0.6493 ± 0.048
Per class
Cross-validation details (10-fold Crossvalidation)
0.5522 ± 0.0582
Cross-validation details (10-fold Crossvalidation)
384.8251 ± 2.1437
Cross-validation details (10-fold Crossvalidation)
0.1884 ± 0.0081
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)
0.6591 ± 0.0536
Per class
Cross-validation details (10-fold Crossvalidation)
0.6535 ± 0.0446
Cross-validation details (10-fold Crossvalidation)
2.2629
Cross-validation details (10-fold Crossvalidation)
0.6535 ± 0.0446
Per class
Cross-validation details (10-fold Crossvalidation)
0.6016 ± 0.0259
Cross-validation details (10-fold Crossvalidation)
0.3957 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.2982 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
0.7537 ± 0.0259
Cross-validation details (10-fold Crossvalidation)