Run
6019531

Run 6019531

Task 3896 (Supervised Classification) ada_agnostic 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[]
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[]
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)_C195.8682354508308
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.289552787970202
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree4
sklearn.svm.classes.SVC(8)_gamma5.5318984503380506e-05
sklearn.svm.classes.SVC(8)_kernel"poly"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state53147
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.020613776520300556
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
0.705 ± 0.0321
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7528 ± 0.0171
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3075 ± 0.0521
Cross-validation details (10-fold Crossvalidation)
KB relative information score
788.2176 ± 21.8983
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2935 ± 0.0165
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3732 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
4562
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7479 ± 0.023
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7683 ± 0.0179
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8085
Cross-validation details (10-fold Crossvalidation)
Recall
0.7683 ± 0.0179
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7866 ± 0.0443
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4319 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.421 ± 0.019
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9746 ± 0.0438
Cross-validation details (10-fold Crossvalidation)