Run
2042010

Run 2042010

Task 11 (Supervised Classification) balance-scale Uploaded 16-04-2017 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_16_02.44.29_2017
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(svc=sklearn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
sklearn.svm.classes.SVC(5)_C512.0
sklearn.svm.classes.SVC(5)_cache_size200
sklearn.svm.classes.SVC(5)_class_weightNone
sklearn.svm.classes.SVC(5)_coef00.0
sklearn.svm.classes.SVC(5)_decision_function_shapeNone
sklearn.svm.classes.SVC(5)_degree3
sklearn.svm.classes.SVC(5)_gamma0.015625
sklearn.svm.classes.SVC(5)_kernelpoly
sklearn.svm.classes.SVC(5)_max_iter-1
sklearn.svm.classes.SVC(5)_probabilityTrue
sklearn.svm.classes.SVC(5)_random_stateNone
sklearn.svm.classes.SVC(5)_shrinkingTrue
sklearn.svm.classes.SVC(5)_tol0.001
sklearn.svm.classes.SVC(5)_verboseFalse
sklearn.pipeline.Pipeline(svc=sklearn.svm.classes.SVC)(1)_steps[('nonetype', None), ('svc', SVC(C=512.0, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma=0.015625, kernel='poly', max_iter=-1, 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
1
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9937
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9888
Cross-validation details (10-fold Crossvalidation)
KB relative information score
565.5088
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0457
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3798
Cross-validation details (10-fold Crossvalidation)
Number of instances
625
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9941
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9936
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.3212
Cross-validation details (10-fold Crossvalidation)
Recall
0.9936
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1202
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4356
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1132
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2599
Cross-validation details (10-fold Crossvalidation)