Run
8809963

Run 8809963

Task 3889 (Supervised Classification) sylva_agnostic Uploaded 23-01-2018 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"median"
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)_C15791.018915538956
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.756322571241518
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree5
sklearn.svm.classes.SVC(17)_gamma0.015620030380378068
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_state9401
sklearn.svm.classes.SVC(17)_shrinkingfalse
sklearn.svm.classes.SVC(17)_tol0.0021523396621208114
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

0.9007 ± 0.0179
Per class
Cross-validation details (10-fold Crossvalidation)
0.9423 ± 0.0041
Per class
Cross-validation details (10-fold Crossvalidation)
0.4073 ± 0.048
Cross-validation details (10-fold Crossvalidation)
3237.9368 ± 54.0559
Cross-validation details (10-fold Crossvalidation)
0.0631 ± 0.0023
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)
0.9552 ± 0.0022
Per class
Cross-validation details (10-fold Crossvalidation)
0.9546 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
0.3338
Cross-validation details (10-fold Crossvalidation)
0.9546 ± 0.0023
Per class
Cross-validation details (10-fold Crossvalidation)
0.5456 ± 0.02
Cross-validation details (10-fold Crossvalidation)
0.2403 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.1885 ± 0.0043
Cross-validation details (10-fold Crossvalidation)
0.7842 ± 0.0177
Cross-validation details (10-fold Crossvalidation)