Run
8825922

Run 8825922

Task 3889 (Supervised Classification) sylva_agnostic Uploaded 24-01-2018 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,scaling=sklea rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S VC)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"mean"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(18)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(18)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(18)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(12)_threshold0.0
sklearn.preprocessing.data.StandardScaler(6)_copytrue
sklearn.preprocessing.data.StandardScaler(6)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(6)_with_stdtrue
sklearn.svm.classes.SVC(17)_C0.20490837145247137
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef0-0.14284364864148946
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree3
sklearn.svm.classes.SVC(17)_gamma0.010655254671154855
sklearn.svm.classes.SVC(17)_kernel"sigmoid"
sklearn.svm.classes.SVC(17)_max_iter-1
sklearn.svm.classes.SVC(17)_probabilitytrue
sklearn.svm.classes.SVC(17)_random_state8321
sklearn.svm.classes.SVC(17)_shrinkingfalse
sklearn.svm.classes.SVC(17)_tol2.6287755001103717e-05
sklearn.svm.classes.SVC(17)_verbosefalse

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

0.5916 ± 0.1435
Per class
Cross-validation details (10-fold Crossvalidation)
0.9153 ± 0.0261
Per class
Cross-validation details (10-fold Crossvalidation)
0.1456 ± 0.149
Cross-validation details (10-fold Crossvalidation)
-12609.6289 ± 2892.6273
Cross-validation details (10-fold Crossvalidation)
0.1277 ± 0.0858
Cross-validation details (10-fold Crossvalidation)
0.1156 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
14395
Per class
Cross-validation details (10-fold Crossvalidation)
0.9067 ± 0.0036
Per class
Cross-validation details (10-fold Crossvalidation)
0.931 ± 0.0269
Cross-validation details (10-fold Crossvalidation)
0.3338
Cross-validation details (10-fold Crossvalidation)
0.931 ± 0.0269
Per class
Cross-validation details (10-fold Crossvalidation)
1.1046 ± 0.7454
Cross-validation details (10-fold Crossvalidation)
0.2403 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.2572 ± 0.052
Cross-validation details (10-fold Crossvalidation)
1.0701 ± 0.218
Cross-validation details (10-fold Crossvalidation)