Run
8816562

Run 8816562

Task 14967 (Supervised Classification) cjs Uploaded 24-01-2018 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1. study_71
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklea rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S VC)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[0, 1]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"mean"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features[0, 1]
sklearn.preprocessing.data.OneHotEncoder(18)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(18)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(18)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(12)_threshold0.0
sklearn.preprocessing.data.StandardScaler(6)_copytrue
sklearn.preprocessing.data.StandardScaler(6)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(6)_with_stdtrue
sklearn.svm.classes.SVC(17)_C12.244976255287396
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.20071448678855242
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree2
sklearn.svm.classes.SVC(17)_gamma0.4646380820639641
sklearn.svm.classes.SVC(17)_kernel"rbf"
sklearn.svm.classes.SVC(17)_max_iter-1
sklearn.svm.classes.SVC(17)_probabilitytrue
sklearn.svm.classes.SVC(17)_random_state12407
sklearn.svm.classes.SVC(17)_shrinkingtrue
sklearn.svm.classes.SVC(17)_tol0.0009185545165285066
sklearn.svm.classes.SVC(17)_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
0.9848 ± 0.0006
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8603 ± 0.0099
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8159 ± 0.0149
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2250.3083 ± 4.9641
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0616 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2729 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
2796
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8949 ± 0.0092
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8484 ± 0.0128
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.5207
Cross-validation details (10-fold Crossvalidation)
Recall
0.8484 ± 0.0128
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2257 ± 0.0214
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3694 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1707 ± 0.0086
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4621 ± 0.0232
Cross-validation details (10-fold Crossvalidation)