Run
6208734

Run 6208734

Task 3904 (Supervised Classification) jm1 Uploaded 27-08-2017 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"mean"
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)_C0.049015318225567234
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.07668729525920726
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.03648653473866884
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_state19776
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.0032699091057232376
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
0.4483 ± 0.1234
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7193 ± 0.0014
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0033 ± 0.0049
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-168.7642 ± 14.7191
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3115 ± 0.0032
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3121 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Number of instances
10885
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6502 ± 0.0008
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8049 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7088
Cross-validation details (10-fold Crossvalidation)
Recall
0.8049 ± 0.0023
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9979 ± 0.0103
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.395 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3965 ± 0.0026
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0036 ± 0.0068
Cross-validation details (10-fold Crossvalidation)