Run
8852716

Run 8852716

Task 31 (Supervised Classification) credit-g Uploaded 27-01-2018 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, 2, 3, 5, 6, 8, 9, 11, 13, 14, 16, 18, 19]
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, 2, 3, 5, 6, 8, 9, 11, 13, 14, 16, 18, 19]
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)_C6032.220156298481
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.6410838081932613
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree2
sklearn.svm.classes.SVC(17)_gamma4.630218307714798
sklearn.svm.classes.SVC(17)_kernel"poly"
sklearn.svm.classes.SVC(17)_max_iter-1
sklearn.svm.classes.SVC(17)_probabilitytrue
sklearn.svm.classes.SVC(17)_random_state38790
sklearn.svm.classes.SVC(17)_shrinkingtrue
sklearn.svm.classes.SVC(17)_tol0.001568519951403031
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
0.7065 ± 0.0436
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6844 ± 0.0354
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2169 ± 0.086
Cross-validation details (10-fold Crossvalidation)
KB relative information score
107.3151 ± 3.2475
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3701 ± 0.0096
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4202
Cross-validation details (10-fold Crossvalidation)
Number of instances
1000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7097 ± 0.0541
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.73 ± 0.0343
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8818
Cross-validation details (10-fold Crossvalidation)
Recall
0.73 ± 0.0343
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8808 ± 0.0229
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4325 ± 0.0146
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9437 ± 0.0318
Cross-validation details (10-fold Crossvalidation)