Run
2087086

Run 2087086

Task 22 (Supervised Classification) mfeat-zernike Uploaded 24-04-2017 by Jeroen van Hoof
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  • Mon_Apr_24_18.59.38_2017 NumPy_1.12.0. Python_3.6.0. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar dScaler,svc=sklearn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
sklearn.svm.classes.SVC(5)_C32.0
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)_gamma0.001953125
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)_tol0.001
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(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_steps[('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('svc', SVC(C=32.0, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma=0.001953125, kernel='rbf', max_iter=-1, probability=True, random_state=3, 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
0.988
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8663
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8528
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1721.7868
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0416
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
0.8655
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8675
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.8675
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.231
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1318
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4394
Cross-validation details (10-fold Crossvalidation)