OpenML
6281685

Run 6281685

Task 146606 (Supervised Classification) higgs Uploaded 28-08-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1.
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"mean"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C0.05932167158120652
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.10631693188003877
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.017562368026848973
sklearn.svm.classes.SVC(8)_kernel"sigmoid"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state49006
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol2.1817555618862674e-05
sklearn.svm.classes.SVC(8)_verbosefalse

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

Area under ROC curve
0.5378 ± 0.0053
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5267 ± 0.0042
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0585 ± 0.0087
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1279.1918 ± 15.3372
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4932 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4984 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
98050
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.5328 ± 0.0047
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5375 ± 0.0044
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9976
Cross-validation details (10-fold Crossvalidation)
Recall
0.5375 ± 0.0044
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9897 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4992 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5002 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0021 ± 0.0016
Cross-validation details (10-fold Crossvalidation)