Run
6281650

Run 6281650

Task 3918 (Supervised Classification) pc1 Uploaded 28-08-2017 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[]
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)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C0.2723243544087971
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef0-0.032944429478052095
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree5
sklearn.svm.classes.SVC(8)_gamma0.00020127138255364248
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_state57245
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.00045875588539248983
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
0.501 ± 0.1062
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.1751
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0008 ± 0.0051
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-8996.5332 ± 313.0998
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.8516 ± 0.2504
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1299 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Number of instances
1109
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8677
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.1542 ± 0.2688
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3667
Cross-validation details (10-fold Crossvalidation)
Recall
0.1542 ± 0.2688
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
6.5565 ± 1.954
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2542 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.9194 ± 0.2182
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
3.6169 ± 0.8762
Cross-validation details (10-fold Crossvalidation)