Run
6140687

Run 6140687

Task 14967 (Supervised Classification) cjs Uploaded 26-08-2017 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[0, 1]
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[0, 1]
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)_C19.23857074444938
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.9514440163989468
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree2
sklearn.svm.classes.SVC(8)_gamma1.6342802606665277
sklearn.svm.classes.SVC(8)_kernel"poly"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state22924
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.06682747345484889
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
1 ± 0
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9986 ± 0.0025
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9983 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2763.7437 ± 1.3047
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0061 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2729 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
2796
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9986 ± 0.0025
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9986 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.5207
Cross-validation details (10-fold Crossvalidation)
Recall
0.9986 ± 0.0025
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0224 ± 0.0046
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3694 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0199 ± 0.0107
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.054 ± 0.029
Cross-validation details (10-fold Crossvalidation)