Run
9189553

Run 9189553

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)_C290.2988833581153
sklearn.svm.classes.SVC(16)_cache_size200
sklearn.svm.classes.SVC(16)_class_weightnull
sklearn.svm.classes.SVC(16)_coef00.483268069671127
sklearn.svm.classes.SVC(16)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(16)_degree3
sklearn.svm.classes.SVC(16)_gamma0.06881601312921554
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_state19693
sklearn.svm.classes.SVC(16)_shrinkingtrue
sklearn.svm.classes.SVC(16)_tol0.08938541645368472
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

0.8389 ± 0.0198
Per class
Cross-validation details (10-fold Crossvalidation)
0.757 ± 0.0314
Per class
Cross-validation details (10-fold Crossvalidation)
0.6884 ± 0.0394
Cross-validation details (10-fold Crossvalidation)
1407.7217 ± 7.0043
Cross-validation details (10-fold Crossvalidation)
0.0693 ± 0.0088
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)
0.7575 ± 0.031
Per class
Cross-validation details (10-fold Crossvalidation)
0.7573 ± 0.0308
Cross-validation details (10-fold Crossvalidation)
2.4138
Cross-validation details (10-fold Crossvalidation)
0.7573 ± 0.0308
Per class
Cross-validation details (10-fold Crossvalidation)
0.3118 ± 0.0395
Cross-validation details (10-fold Crossvalidation)
0.3334 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.2633 ± 0.0174
Cross-validation details (10-fold Crossvalidation)
0.7899 ± 0.0521
Cross-validation details (10-fold Crossvalidation)