Run
5896171

Run 5896171

Task 3561 (Supervised Classification) profb 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[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"median"
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)_C525.9551709664082
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.07500471526744401
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.0014026629028670973
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_state52943
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.0005417943589362689
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
0.5083 ± 0.0937
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5319 ± 0.0135
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0059 ± 0.0124
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-3.9235 ± 2.7167
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4416 ± 0.0162
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
0.4438 ± 0.0141
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6637 ± 0.01
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9188
Cross-validation details (10-fold Crossvalidation)
Recall
0.6637 ± 0.01
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9932 ± 0.0333
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
0.4733 ± 0.0036
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0039 ± 0.0082
Cross-validation details (10-fold Crossvalidation)