Run
5900363

Run 5900363

Task 11 (Supervised Classification) balance-scale Uploaded 13-07-2017 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)_C389.67940039721003
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.7439065921802708
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.006039379525120629
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_state38450
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.009534792341245586
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
0.9398 ± 0.0196
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8089 ± 0.0407
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6935 ± 0.0542
Cross-validation details (10-fold Crossvalidation)
KB relative information score
352.5711 ± 2.3806
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1696 ± 0.0146
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3798 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Number of instances
625
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8223 ± 0.0529
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8336 ± 0.0291
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.3212
Cross-validation details (10-fold Crossvalidation)
Recall
0.8336 ± 0.0291
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4466 ± 0.0378
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4356 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2792 ± 0.0189
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6411 ± 0.0425
Cross-validation details (10-fold Crossvalidation)