Run
5977498

Run 5977498

Task 14967 (Supervised Classification) cjs Uploaded 16-07-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1. study_71
Issue #Downvotes for this reason By


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_features0.264521604362817
sklearn.ensemble.forest.RandomForestClassifier(21)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(21)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_leaf8
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_split4
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_state16851
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, 1]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"mean"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[0, 1]
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

0.9989 ± 0.0005
Per class
Cross-validation details (10-fold Crossvalidation)
0.9726 ± 0.0101
Per class
Cross-validation details (10-fold Crossvalidation)
0.966 ± 0.0125
Cross-validation details (10-fold Crossvalidation)
2553.4956 ± 3.0837
Cross-validation details (10-fold Crossvalidation)
0.0353 ± 0.0034
Cross-validation details (10-fold Crossvalidation)
0.2729 ± 0
Cross-validation details (10-fold Crossvalidation)
2796
Per class
Cross-validation details (10-fold Crossvalidation)
0.9742 ± 0.0094
Per class
Cross-validation details (10-fold Crossvalidation)
0.9721 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
2.5207
Cross-validation details (10-fold Crossvalidation)
0.9721 ± 0.0102
Per class
Cross-validation details (10-fold Crossvalidation)
0.1292 ± 0.0123
Cross-validation details (10-fold Crossvalidation)
0.3694 ± 0
Cross-validation details (10-fold Crossvalidation)
0.1014 ± 0.0079
Cross-validation details (10-fold Crossvalidation)
0.2745 ± 0.0213
Cross-validation details (10-fold Crossvalidation)