Run
8979171

Run 8979171

Task 3493 (Supervised Classification) monks-problems-2 Uploaded 08-04-2018 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,scaling=sklea rn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_sele ction.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.S VC)(2)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"mean"
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)_C9688.20131283193
sklearn.svm.classes.SVC(11)_cache_size200
sklearn.svm.classes.SVC(11)_class_weightnull
sklearn.svm.classes.SVC(11)_coef0-0.1357185441890827
sklearn.svm.classes.SVC(11)_decision_function_shapenull
sklearn.svm.classes.SVC(11)_degree3
sklearn.svm.classes.SVC(11)_gamma1.1908487718919176e-05
sklearn.svm.classes.SVC(11)_kernel"sigmoid"
sklearn.svm.classes.SVC(11)_max_iter-1
sklearn.svm.classes.SVC(11)_probabilitytrue
sklearn.svm.classes.SVC(11)_random_state1266
sklearn.svm.classes.SVC(11)_shrinkingtrue
sklearn.svm.classes.SVC(11)_tol0.0019173857432287099
sklearn.svm.classes.SVC(11)_verbosefalse
sklearn.preprocessing.data.StandardScaler(7)_copytrue
sklearn.preprocessing.data.StandardScaler(7)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(7)_with_stdtrue

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
0.5743 ± 0.0618
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5438 ± 0.0253
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0238 ± 0.0443
Cross-validation details (10-fold Crossvalidation)
KB relative information score
6.8192 ± 1.4647
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4412 ± 0.0083
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
0.6062 ± 0.1242
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6572 ± 0.0152
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9279
Cross-validation details (10-fold Crossvalidation)
Recall
0.6572 ± 0.0152
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9789 ± 0.0156
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
0.4696 ± 0.0096
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9894 ± 0.0169
Cross-validation details (10-fold Crossvalidation)