Run
5971158

Run 5971158

Task 3561 (Supervised Classification) profb Uploaded 16-07-2017 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[3, 4, 7, 8]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[3, 4, 7, 8]
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)_C113.3617777314225
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.40257267667191177
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree5
sklearn.svm.classes.SVC(8)_gamma0.278319751500403
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_state13565
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol4.4236039455682314e-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
0.6715 ± 0.0667
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6111 ± 0.0518
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1143 ± 0.1174
Cross-validation details (10-fold Crossvalidation)
KB relative information score
54.2359 ± 2.9534
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4065 ± 0.0144
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4446 ± 0.0022
Cross-validation details (10-fold Crossvalidation)
Number of instances
672
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.645 ± 0.0966
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6771 ± 0.0401
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9188
Cross-validation details (10-fold Crossvalidation)
Recall
0.6771 ± 0.0401
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9143 ± 0.034
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4543 ± 0.0152
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9636 ± 0.034
Cross-validation details (10-fold Crossvalidation)