Run
2014002

Run 2014002

Task 18 (Supervised Classification) mfeat-morphological Uploaded 08-04-2017 by Jeroen van Hoof
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  • NumPy_1.12.0. Python_3.6.0. run_task Sat_Apr__8_02.21.38_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)_C6602.22362885
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)_gamma0.000690148074215
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)_tol0.01
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=6602.2236288509312, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma=0.00069014807421490215, kernel='rbf', max_iter=-1, probability=True, random_state=3, 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
0.9678
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7516
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.725
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1505.5143
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0697
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
0.7534
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7525
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.7525
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3872
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1795
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5983
Cross-validation details (10-fold Crossvalidation)