Run
2012938

Run 2012938

Task 59 (Supervised Classification) iris Uploaded 06-04-2017 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. Thu_Apr__6_23.12.22_2017
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,stand ardscaler=sklearn.preprocessing.data.StandardScaler,nusvc=sklearn.svm.class es.NuSVC)(1)Automatically created scikit-learn flow.
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)_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,standardscaler=sklearn.preprocessing.data.StandardScaler,nusvc=sklearn.svm.classes.NuSVC)(1)_steps[('dualimputer', ), ('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='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
0.9984
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9733
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.96
Cross-validation details (10-fold Crossvalidation)
KB relative information score
135.6615
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0578
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4444
Cross-validation details (10-fold Crossvalidation)
Number of instances
150
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9738
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9733
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.9733
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1302
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1237
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2624
Cross-validation details (10-fold Crossvalidation)