Run
5827850

Run 5827850

Task 3913 (Supervised Classification) kc2 Uploaded 13-07-2017 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)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C1190.0375069501704
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.0
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.010738422887295863
sklearn.svm.classes.SVC(8)_kernel"rbf"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state6068
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol0.007488724587102887
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
0.6969 ± 0.0892
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6995 ± 0.0131
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0186 ± 0.0248
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-25.2746 ± 6.8347
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2996 ± 0.0275
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3266 ± 0.0052
Cross-validation details (10-fold Crossvalidation)
Number of instances
522
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6305 ± 0.017
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7854 ± 0.0126
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.734
Cross-validation details (10-fold Crossvalidation)
Recall
0.7854 ± 0.0126
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9172 ± 0.0822
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4037 ± 0.0065
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3877 ± 0.0213
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9603 ± 0.0499
Cross-validation details (10-fold Crossvalidation)