Run
2012948

Run 2012948

Task 23 (Supervised Classification) cmc Uploaded 07-04-2017 by Jeroen van Hoof
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  • Fri_Apr__7_02.43.59_2017 NumPy_1.12.1. Python_3.5.3. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,oneho tencoder=sklearn.preprocessing.data.OneHotEncoder,nusvc=sklearn.svm.classes .NuSVC)(1)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(3)_categorical_features[False, True, True, False, True, True, True, True, True]
sklearn.preprocessing.data.OneHotEncoder(3)_dtype
sklearn.preprocessing.data.OneHotEncoder(3)_handle_unknownerror
sklearn.preprocessing.data.OneHotEncoder(3)_n_valuesauto
sklearn.preprocessing.data.OneHotEncoder(3)_sparseTrue
sklearn.svm.classes.NuSVC(1)_cache_size200
sklearn.svm.classes.NuSVC(1)_class_weightNone
sklearn.svm.classes.NuSVC(1)_coef00.0
sklearn.svm.classes.NuSVC(1)_decision_function_shapeNone
sklearn.svm.classes.NuSVC(1)_degree3
sklearn.svm.classes.NuSVC(1)_gammaauto
sklearn.svm.classes.NuSVC(1)_kernellinear
sklearn.svm.classes.NuSVC(1)_max_iter-1
sklearn.svm.classes.NuSVC(1)_nu0.3
sklearn.svm.classes.NuSVC(1)_probabilityTrue
sklearn.svm.classes.NuSVC(1)_random_stateNone
sklearn.svm.classes.NuSVC(1)_shrinkingTrue
sklearn.svm.classes.NuSVC(1)_tol0.001
sklearn.svm.classes.NuSVC(1)_verboseFalse
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,nusvc=sklearn.svm.classes.NuSVC)(1)_steps[('dualimputer', ), ('onehotencoder', OneHotEncoder(categorical_features=[False, True, True, False, True, True, True, True, True], dtype=, handle_unknown='error', n_values='auto', sparse=True)), ('nusvc', NuSVC(cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma='auto', kernel='linear', max_iter=-1, nu=0.3, probability=True, random_state=None, shrinking=True, tol=0.001, verbose=False))]

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
0.542
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.2818
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0088
Cross-validation details (10-fold Crossvalidation)
KB relative information score
25.3474
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4303
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4308
Cross-validation details (10-fold Crossvalidation)
Number of instances
1473
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.3073
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4168
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5392
Cross-validation details (10-fold Crossvalidation)
Recall
0.4168
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9988
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4641
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4649
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0017
Cross-validation details (10-fold Crossvalidation)