Run
6208431

Run 6208431

Task 3485 (Supervised Classification) scene Uploaded 27-08-2017 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)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C1.5920103429477819
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.42089922435699
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.07608946865098518
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_state47023
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.025606364616512146
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
0.9834 ± 0.0158
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9787 ± 0.0115
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9273 ± 0.0402
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2089.2958 ± 10.0867
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0378 ± 0.009
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
0.9787 ± 0.0115
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9788 ± 0.0113
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.6786
Cross-validation details (10-fold Crossvalidation)
Recall
0.9788 ± 0.0113
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1284 ± 0.0308
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
0.1334 ± 0.031
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.348 ± 0.0811
Cross-validation details (10-fold Crossvalidation)