Run
5997579

Run 5997579

Task 3485 (Supervised Classification) scene Uploaded 17-07-2017 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[294, 295, 296, 297, 298]
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[294, 295, 296, 297, 298]
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)_C17926.21472428695
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.938799514039981
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.006292977182837713
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_state2010
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol5.840872697841438e-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
0.9584 ± 0.0204
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9379 ± 0.0184
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7855 ± 0.0616
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1639.6964 ± 13.4162
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0875 ± 0.0115
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2942 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Number of instances
2407
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9375 ± 0.0188
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9389 ± 0.0188
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.6786
Cross-validation details (10-fold Crossvalidation)
Recall
0.9389 ± 0.0188
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2974 ± 0.0394
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3834 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2184 ± 0.0296
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5697 ± 0.0778
Cross-validation details (10-fold Crossvalidation)