Run
5970977

Run 5970977

Task 3493 (Supervised Classification) monks-problems-2 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[0, 1, 2, 3, 4, 5]
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[0, 1, 2, 3, 4, 5]
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)_C958.5827284111751
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.04288402538223335
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma6.64917042634297e-05
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_state44300
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol8.357227139379805e-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
0.6504 ± 0.0691
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5304 ± 0.0404
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0113 ± 0.0611
Cross-validation details (10-fold Crossvalidation)
KB relative information score
24.2001 ± 1.9555
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.428 ± 0.0104
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4507 ± 0.0026
Cross-validation details (10-fold Crossvalidation)
Number of instances
601
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.5285 ± 0.0928
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6423 ± 0.0278
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9279
Cross-validation details (10-fold Crossvalidation)
Recall
0.6423 ± 0.0278
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9496 ± 0.0231
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4746 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4628 ± 0.0098
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.975 ± 0.0204
Cross-validation details (10-fold Crossvalidation)