OpenML
8709997

Run 8709997

Task 3904 (Supervised Classification) jm1 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[]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features[]
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)_C4030.866659947034
sklearn.svm.classes.SVC(17)_cache_size200
sklearn.svm.classes.SVC(17)_class_weightnull
sklearn.svm.classes.SVC(17)_coef00.7946045798569932
sklearn.svm.classes.SVC(17)_decision_function_shapenull
sklearn.svm.classes.SVC(17)_degree1
sklearn.svm.classes.SVC(17)_gamma0.003402062245500771
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_state32272
sklearn.svm.classes.SVC(17)_shrinkingtrue
sklearn.svm.classes.SVC(17)_tol7.185490823789343e-05
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
0.6781 ± 0.0209
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7387 ± 0.0074
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0644 ± 0.0271
Cross-validation details (10-fold Crossvalidation)
KB relative information score
435.2149 ± 10.9786
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2977 ± 0.0024
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
0.7766 ± 0.0198
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8103 ± 0.0034
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7088
Cross-validation details (10-fold Crossvalidation)
Recall
0.8103 ± 0.0034
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9537 ± 0.0077
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
0.3861 ± 0.0029
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9773 ± 0.0075
Cross-validation details (10-fold Crossvalidation)