Run
1985175

Run 1985175

Task 18 (Supervised Classification) mfeat-morphological Uploaded 05-04-2017 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. Wed_Apr__5_13.56.52_2017
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)_C36694.330516
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)_gamma0.00131788094533
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)_tol6.07881336915e-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=36694.330515978741, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma=0.0013178809453347608, kernel='rbf', max_iter=-1, probability=True, random_state=3, shrinking=True, tol=6.0788133691514437e-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
0.9677
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.75
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7239
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1506.1297
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0699
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7519
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7515
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.7515
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3883
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1789
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5965
Cross-validation details (10-fold Crossvalidation)