Run
9188551

Run 9188551

Task 167119 (Supervised Classification) jungle_chess_2pcs_raw_endgame_complete Uploaded 16-04-2018 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 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)_C58.9590256458544
sklearn.svm.classes.SVC(16)_cache_size200
sklearn.svm.classes.SVC(16)_class_weightnull
sklearn.svm.classes.SVC(16)_coef00.9779024162257908
sklearn.svm.classes.SVC(16)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(16)_degree3
sklearn.svm.classes.SVC(16)_gamma0.0012787928867369442
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_state32384
sklearn.svm.classes.SVC(16)_shrinkingtrue
sklearn.svm.classes.SVC(16)_tol7.04294760709383e-05
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.

15 Evaluation measures

Area under ROC curve
0.7693 ± 0.0042
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5416 ± 0.0085
Cross-validation details (10-fold Crossvalidation)
KB relative information score
23365.3626 ± 31.0337
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1643 ± 0.003
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3832 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
44819
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7535 ± 0.0046
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.3491
Cross-validation details (10-fold Crossvalidation)
Recall
0.7535 ± 0.0046
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4288 ± 0.0079
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4377 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4053 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9261 ± 0.0085
Cross-validation details (10-fold Crossvalidation)