Run
2036041

Run 2036041

Task 37 (Supervised Classification) diabetes Uploaded 08-04-2017 by Jeroen van Hoof
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  • NumPy_1.12.1. Python_3.5.3. run_task Sat_Apr__8_22.35.47_2017 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,stand ardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes .SVC)(1)Automatically created scikit-learn flow.
sklearn.svm.classes.SVC(5)_C220.823923152
sklearn.svm.classes.SVC(5)_cache_size1000
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)_gamma0.000107438654041
sklearn.svm.classes.SVC(5)_kernelrbf
sklearn.svm.classes.SVC(5)_max_iter-1
sklearn.svm.classes.SVC(5)_probabilityTrue
sklearn.svm.classes.SVC(5)_random_state3
sklearn.svm.classes.SVC(5)_shrinkingTrue
sklearn.svm.classes.SVC(5)_tol1.78387970737e-05
sklearn.svm.classes.SVC(5)_verboseFalse
sklearn.preprocessing.data.StandardScaler(1)_copyTrue
sklearn.preprocessing.data.StandardScaler(1)_with_meanTrue
sklearn.preprocessing.data.StandardScaler(1)_with_stdTrue
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_steps[('DualImputer', ), ('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('svc', SVC(C=220.82392315216396, cache_size=1000, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma=0.00010743865404126471, kernel='rbf', max_iter=-1, probability=True, random_state=3, shrinking=True, tol=1.783879707365308e-05, 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
0.8272
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7638
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4692
Cross-validation details (10-fold Crossvalidation)
KB relative information score
244.4881
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3175
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4545
Cross-validation details (10-fold Crossvalidation)
Number of instances
768
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.769
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7734
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9335
Cross-validation details (10-fold Crossvalidation)
Recall
0.7734
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6985
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4766
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3977
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8343
Cross-validation details (10-fold Crossvalidation)