Run
7576346

Run 7576346

Task 3494 (Supervised Classification) monks-problems-3 Uploaded 07-09-2017 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)(3)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(5)_axis0
openmlstudy14.preprocessing.ConditionalImputer(5)_categorical_features[0, 1, 2, 3, 4, 5]
openmlstudy14.preprocessing.ConditionalImputer(5)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(5)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(5)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_verbose0
sklearn.preprocessing.data.OneHotEncoder(9)_categorical_features[0, 1, 2, 3, 4, 5]
sklearn.preprocessing.data.OneHotEncoder(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(9)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(9)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(9)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(7)_threshold0.0
sklearn.svm.classes.SVC(11)_C2.4880861659431814
sklearn.svm.classes.SVC(11)_cache_size200
sklearn.svm.classes.SVC(11)_class_weightnull
sklearn.svm.classes.SVC(11)_coef0-0.30206050607692925
sklearn.svm.classes.SVC(11)_decision_function_shapenull
sklearn.svm.classes.SVC(11)_degree3
sklearn.svm.classes.SVC(11)_gamma3.3666623597788234
sklearn.svm.classes.SVC(11)_kernel"rbf"
sklearn.svm.classes.SVC(11)_max_iter-1
sklearn.svm.classes.SVC(11)_probabilitytrue
sklearn.svm.classes.SVC(11)_random_state30655
sklearn.svm.classes.SVC(11)_shrinkingtrue
sklearn.svm.classes.SVC(11)_tol0.0008820771893151229
sklearn.svm.classes.SVC(11)_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
0.8367 ± 0.0463
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7057 ± 0.0986
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4274 ± 0.1727
Cross-validation details (10-fold Crossvalidation)
KB relative information score
183.5476 ± 3.5317
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3403 ± 0.0292
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4992 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
554
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7505 ± 0.0598
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7184 ± 0.0852
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9989
Cross-validation details (10-fold Crossvalidation)
Recall
0.7184 ± 0.0852
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6816 ± 0.0588
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4996 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4093 ± 0.0303
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8193 ± 0.0611
Cross-validation details (10-fold Crossvalidation)