Run
9189490

Run 9189490

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)_C436.76411392274053
sklearn.svm.classes.SVC(16)_cache_size200
sklearn.svm.classes.SVC(16)_class_weightnull
sklearn.svm.classes.SVC(16)_coef00.966487007743914
sklearn.svm.classes.SVC(16)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(16)_degree3
sklearn.svm.classes.SVC(16)_gamma0.0385792898769548
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_state98228
sklearn.svm.classes.SVC(16)_shrinkingfalse
sklearn.svm.classes.SVC(16)_tol0.00033015772368828283
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

0.8297 ± 0.0185
Per class
Cross-validation details (10-fold Crossvalidation)
0.742 ± 0.029
Per class
Cross-validation details (10-fold Crossvalidation)
0.6703 ± 0.0357
Cross-validation details (10-fold Crossvalidation)
1377.9282 ± 6.142
Cross-validation details (10-fold Crossvalidation)
0.0735 ± 0.008
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)
0.7431 ± 0.0309
Per class
Cross-validation details (10-fold Crossvalidation)
0.7429 ± 0.028
Cross-validation details (10-fold Crossvalidation)
2.4138
Cross-validation details (10-fold Crossvalidation)
0.7429 ± 0.028
Per class
Cross-validation details (10-fold Crossvalidation)
0.3304 ± 0.036
Cross-validation details (10-fold Crossvalidation)
0.3334 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.271 ± 0.0153
Cross-validation details (10-fold Crossvalidation)
0.813 ± 0.0459
Cross-validation details (10-fold Crossvalidation)