Run
9202988

Run 9202988

Task 3512 (Supervised Classification) synthetic_control Uploaded 31-05-2018 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[]
openmlstudy14.preprocessing.ConditionalImputer(5)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(5)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(5)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(5)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(5)_verbose0
sklearn.preprocessing.data.OneHotEncoder(9)_categorical_features[]
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)_C1.9004093116996186
sklearn.svm.classes.SVC(11)_cache_size200
sklearn.svm.classes.SVC(11)_class_weightnull
sklearn.svm.classes.SVC(11)_coef00.7821061854274951
sklearn.svm.classes.SVC(11)_decision_function_shapenull
sklearn.svm.classes.SVC(11)_degree2
sklearn.svm.classes.SVC(11)_gamma0.0005267082853516583
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_state2679
sklearn.svm.classes.SVC(11)_shrinkingfalse
sklearn.svm.classes.SVC(11)_tol0.0005309800769745323
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
0.8578 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6334 ± 0.0427
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6 ± 0.0452
Cross-validation details (10-fold Crossvalidation)
KB relative information score
270.3241 ± 0.2298
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2036 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2778
Cross-validation details (10-fold Crossvalidation)
Number of instances
600
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6859 ± 0.0538
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6667 ± 0.0377
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.6667 ± 0.0377
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7328 ± 0.0034
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3727
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3001 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8053 ± 0.0038
Cross-validation details (10-fold Crossvalidation)