OpenML
8709902

Run 8709902

Task 9977 (Supervised Classification) nomao Uploaded 28-12-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1. study_71
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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)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[6, 7, 14, 15, 22, 23, 30, 31, 38, 39, 46, 47, 54, 55, 62, 63, 70, 71, 78, 79, 86, 87, 91, 95, 99, 103, 107, 111, 115]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features[6, 7, 14, 15, 22, 23, 30, 31, 38, 39, 46, 47, 54, 55, 62, 63, 70, 71, 78, 79, 86, 87, 91, 95, 99, 103, 107, 111, 115]
sklearn.preprocessing.data.OneHotEncoder(18)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(18)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(18)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(12)_threshold0.0
sklearn.preprocessing.data.StandardScaler(6)_copytrue
sklearn.preprocessing.data.StandardScaler(6)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(6)_with_stdtrue
sklearn.svm.classes.SVC(17)_C1.9273770454578472
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef0-0.8388355993073522
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree1
sklearn.svm.classes.SVC(17)_gamma0.0008697547071670999
sklearn.svm.classes.SVC(17)_kernel"poly"
sklearn.svm.classes.SVC(17)_max_iter-1
sklearn.svm.classes.SVC(17)_probabilitytrue
sklearn.svm.classes.SVC(17)_random_state15734
sklearn.svm.classes.SVC(17)_shrinkingfalse
sklearn.svm.classes.SVC(17)_tol0.0012600407402409938
sklearn.svm.classes.SVC(17)_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
0.986 ± 0.0013
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9443 ± 0.0028
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8633 ± 0.007
Cross-validation details (10-fold Crossvalidation)
KB relative information score
27879.2685 ± 23.4535
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0791 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4081 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
34465
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9442 ± 0.0028
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9443 ± 0.0028
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.863
Cross-validation details (10-fold Crossvalidation)
Recall
0.9443 ± 0.0028
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1937 ± 0.0066
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4517 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1999 ± 0.0049
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4425 ± 0.0108
Cross-validation details (10-fold Crossvalidation)