Run
9061247

Run 9061247

Task 167119 (Supervised Classification) jungle_chess_2pcs_raw_endgame_complete Uploaded 12-04-2018 by Hilde Weerts
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  • openml-python Sklearn_0.19.1. study_98
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Flow

sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.Condition alImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=skle arn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sel ection.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)_C0.061420586738652375
sklearn.svm.classes.SVC(16)_cache_size200
sklearn.svm.classes.SVC(16)_class_weightnull
sklearn.svm.classes.SVC(16)_coef00.04874330521918768
sklearn.svm.classes.SVC(16)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(16)_degree3
sklearn.svm.classes.SVC(16)_gamma5.606187391181606e-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_state1
sklearn.svm.classes.SVC(16)_shrinkingfalse
sklearn.svm.classes.SVC(16)_tol1.5666544653198165e-05
sklearn.svm.classes.SVC(16)_verbosefalse
hyperimp.utils.preprocessing.ConditionalImputer(1)_axis0
hyperimp.utils.preprocessing.ConditionalImputer(1)_categorical_features[]
hyperimp.utils.preprocessing.ConditionalImputer(1)_copytrue
hyperimp.utils.preprocessing.ConditionalImputer(1)_fill_empty0
hyperimp.utils.preprocessing.ConditionalImputer(1)_missing_values"NaN"
hyperimp.utils.preprocessing.ConditionalImputer(1)_strategy"mean"
hyperimp.utils.preprocessing.ConditionalImputer(1)_strategy_nominal"most_frequent"
hyperimp.utils.preprocessing.ConditionalImputer(1)_verbose0
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,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.

15 Evaluation measures

0.5
Per class
Cross-validation details (10-fold Crossvalidation)
6745.3527 ± 0.4242
Cross-validation details (10-fold Crossvalidation)
0.3236 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.3832 ± 0
Cross-validation details (10-fold Crossvalidation)
44819
Per class
Cross-validation details (10-fold Crossvalidation)
0.5146 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
1.3491
Cross-validation details (10-fold Crossvalidation)
0.5146 ± 0.0001
Per class
Cross-validation details (10-fold Crossvalidation)
0.8446 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.4377 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5689 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
1.2997 ± 0.0001
Cross-validation details (10-fold Crossvalidation)