Run
2039771

Run 2039771

Task 3492 (Supervised Classification) monks-problems-1 Uploaded 09-04-2017 by Jeroen van Hoof
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  • NumPy_1.12.0. Python_3.6.0. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1. Sun_Apr__9_04.49.59_2017
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(DualImputer=helper.dual_imputer.DualImputer,oneho tencoder=sklearn.preprocessing.data.OneHotEncoder,standardscaler=sklearn.pr eprocessing.data.StandardScaler,nusvc=sklearn.svm.classes.NuSVC)(1)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(3)_categorical_features[True, True, True, True, True, True]
sklearn.preprocessing.data.OneHotEncoder(3)_dtype
sklearn.preprocessing.data.OneHotEncoder(3)_handle_unknownignore
sklearn.preprocessing.data.OneHotEncoder(3)_n_valuesauto
sklearn.preprocessing.data.OneHotEncoder(3)_sparseFalse
sklearn.preprocessing.data.StandardScaler(1)_copyTrue
sklearn.preprocessing.data.StandardScaler(1)_with_meanTrue
sklearn.preprocessing.data.StandardScaler(1)_with_stdTrue
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)_kernelpoly
sklearn.svm.classes.NuSVC(1)_max_iter-1
sklearn.svm.classes.NuSVC(1)_nu0.4
sklearn.svm.classes.NuSVC(1)_probabilityTrue
sklearn.svm.classes.NuSVC(1)_random_state3
sklearn.svm.classes.NuSVC(1)_shrinkingTrue
sklearn.svm.classes.NuSVC(1)_tol0.00205526212883
sklearn.svm.classes.NuSVC(1)_verboseFalse
sklearn.pipeline.Pipeline(DualImputer=helper.dual_imputer.DualImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,standardscaler=sklearn.preprocessing.data.StandardScaler,nusvc=sklearn.svm.classes.NuSVC)(1)_steps[('DualImputer', ), ('onehotencoder', OneHotEncoder(categorical_features=[True, True, True, True, True, True], dtype=, handle_unknown='ignore', n_values='auto', sparse=False)), ('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('nusvc', NuSVC(cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma='auto', kernel='poly', max_iter=-1, nu=0.4, probability=True, random_state=3, shrinking=True, tol=0.0020552621288301618, 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
1
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
1
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
1
Cross-validation details (10-fold Crossvalidation)
KB relative information score
553.2708
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0034
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.5
Cross-validation details (10-fold Crossvalidation)
Number of instances
556
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
1
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
1
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1
Cross-validation details (10-fold Crossvalidation)
Recall
1
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0068
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.5
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0035
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.007
Cross-validation details (10-fold Crossvalidation)