Run
6019006

Run 6019006

Task 31 (Supervised Classification) credit-g Uploaded 18-07-2017 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[0, 2, 3, 5, 6, 8, 9, 11, 13, 14, 16, 18, 19]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[0, 2, 3, 5, 6, 8, 9, 11, 13, 14, 16, 18, 19]
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)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C0.5556517206209769
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.0
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.00010267846016024264
sklearn.svm.classes.SVC(8)_kernel"rbf"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state62929
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol6.275643951894047e-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
0.549 ± 0.0799
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5744 ± 0.0025
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0132 ± 0.0186
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-3.1497 ± 2.6034
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.419 ± 0.0063
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
0.5186 ± 0.0235
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.692 ± 0.0132
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8818
Cross-validation details (10-fold Crossvalidation)
Recall
0.692 ± 0.0132
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9972 ± 0.0149
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.459 ± 0.0074
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0016 ± 0.0161
Cross-validation details (10-fold Crossvalidation)