Run
2039498

Run 2039498

Task 15 (Supervised Classification) breast-w Uploaded 09-04-2017 by Jeroen van Hoof
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Client side error: 'LinearSVC' object has no attribute 'predict_proba'
Evaluation Engine Exception: Required output files not present (e.g., arff predictions).
  • NumPy_1.12.1. Python_3.5.3. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1. Sun_Apr__9_00.40.51_2017
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(DualImputer=helper.dual_imputer.DualImputer,stand ardscaler=sklearn.preprocessing.data.StandardScaler,linearsvc=sklearn.svm.c lasses.LinearSVC)(1)Automatically created scikit-learn flow.
sklearn.svm.classes.LinearSVC(2)_C0.00125761894644
sklearn.svm.classes.LinearSVC(2)_class_weightNone
sklearn.svm.classes.LinearSVC(2)_dualFalse
sklearn.svm.classes.LinearSVC(2)_fit_interceptTrue
sklearn.svm.classes.LinearSVC(2)_intercept_scaling1
sklearn.svm.classes.LinearSVC(2)_losssquared_hinge
sklearn.svm.classes.LinearSVC(2)_max_iter1000
sklearn.svm.classes.LinearSVC(2)_multi_classovr
sklearn.svm.classes.LinearSVC(2)_penaltyl2
sklearn.svm.classes.LinearSVC(2)_random_state3
sklearn.svm.classes.LinearSVC(2)_tol1.45713277581e-05
sklearn.svm.classes.LinearSVC(2)_verbose0
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,linearsvc=sklearn.svm.classes.LinearSVC)(1)_steps[('DualImputer', ), ('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('linearsvc', LinearSVC(C=0.00125761894643793, class_weight=None, dual=False, fit_intercept=True, intercept_scaling=1, loss='squared_hinge', max_iter=1000, multi_class='ovr', penalty='l2', random_state=3, tol=1.4571327758146869e-05, verbose=0))]

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

0 Evaluation measures