Run
9189530

Run 9189530

Task 146817 (Supervised Classification) steel-plates-fault Uploaded 17-04-2018 by Hilde Weerts
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  • openml-python Sklearn_0.19.1. study_98
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.Condition alImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=skl earn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_se lection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1 )Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(17)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(17)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(17)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(17)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(17)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(11)_threshold0.0
sklearn.preprocessing.data.StandardScaler(5)_copytrue
sklearn.preprocessing.data.StandardScaler(5)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(5)_with_stdtrue
sklearn.svm.classes.SVC(16)_C1413.0453449025556
sklearn.svm.classes.SVC(16)_cache_size200
sklearn.svm.classes.SVC(16)_class_weightnull
sklearn.svm.classes.SVC(16)_coef00.567830180445956
sklearn.svm.classes.SVC(16)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(16)_degree3
sklearn.svm.classes.SVC(16)_gamma8.306780029410503e-05
sklearn.svm.classes.SVC(16)_kernel"rbf"
sklearn.svm.classes.SVC(16)_max_iter-1
sklearn.svm.classes.SVC(16)_probabilityfalse
sklearn.svm.classes.SVC(16)_random_state39653
sklearn.svm.classes.SVC(16)_shrinkingtrue
sklearn.svm.classes.SVC(16)_tol0.0011255476360563306
sklearn.svm.classes.SVC(16)_verbosefalse
hyperimp.utils.preprocessing.ConditionalImputer2(1)_axis0
hyperimp.utils.preprocessing.ConditionalImputer2(1)_categorical_features[]
hyperimp.utils.preprocessing.ConditionalImputer2(1)_copytrue
hyperimp.utils.preprocessing.ConditionalImputer2(1)_fill_empty0
hyperimp.utils.preprocessing.ConditionalImputer2(1)_missing_values"NaN"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_strategy"mean"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_strategy_nominal"most_frequent"
hyperimp.utils.preprocessing.ConditionalImputer2(1)_verbose0
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1)_memorynull

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

0.8085 ± 0.0172
Per class
Cross-validation details (10-fold Crossvalidation)
0.7165 ± 0.0241
Per class
Cross-validation details (10-fold Crossvalidation)
0.6335 ± 0.031
Cross-validation details (10-fold Crossvalidation)
1305.9195 ± 5.2858
Cross-validation details (10-fold Crossvalidation)
0.081 ± 0.0068
Cross-validation details (10-fold Crossvalidation)
0.2223 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
1941
Per class
Cross-validation details (10-fold Crossvalidation)
0.7204 ± 0.0229
Per class
Cross-validation details (10-fold Crossvalidation)
0.7166 ± 0.0237
Cross-validation details (10-fold Crossvalidation)
2.4138
Cross-validation details (10-fold Crossvalidation)
0.7166 ± 0.0237
Per class
Cross-validation details (10-fold Crossvalidation)
0.3641 ± 0.0303
Cross-validation details (10-fold Crossvalidation)
0.3334 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.2845 ± 0.012
Cross-validation details (10-fold Crossvalidation)
0.8535 ± 0.0358
Cross-validation details (10-fold Crossvalidation)