Run
2007913

Run 2007913

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_17.58.48_2017
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,varia ncethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold ,svc=sklearn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
sklearn.svm.classes.SVC(5)_C100000
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)_gamma0.1
sklearn.svm.classes.SVC(5)_kernellinear
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)_tol0.01
sklearn.svm.classes.SVC(5)_verboseFalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(2)_threshold0.03
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,svc=sklearn.svm.classes.SVC)(1)_steps[('dualimputer', ), ('variancethreshold', VarianceThreshold(threshold=0.03)), ('svc', SVC(C=100000, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma=0.1, kernel='linear', max_iter=-1, probability=True, random_state=None, shrinking=True, tol=0.01, 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
0.9917
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.96
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.94
Cross-validation details (10-fold Crossvalidation)
KB relative information score
127.303
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0901
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
0.96
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.96
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.96
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2026
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1689
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3583
Cross-validation details (10-fold Crossvalidation)