Run
1969625

Run 1969625

Task 49 (Supervised Classification) tic-tac-toe Uploaded 03-04-2017 by Jeroen van Hoof
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Client side error: predict_proba is not available when probability=False
Evaluation Engine Exception: Required output files not present (e.g., arff predictions).
  • Mon_Apr__3_12.18.00_2017 NumPy_1.12.1. Python_3.5.3. run_task SciPy_0.18.1. 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)_C334.500282522
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)_gamma0.1
sklearn.svm.classes.SVC(5)_kernelrbf
sklearn.svm.classes.SVC(5)_max_iter-1
sklearn.svm.classes.SVC(5)_probabilityFalse
sklearn.svm.classes.SVC(5)_random_stateNone
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(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=334.50028252189111, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma=0.10000000000000001, kernel='rbf', max_iter=-1, probability=False, random_state=None, shrinking=True, tol=0.001, verbose=False))]

Result files

xml
Description

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

0 Evaluation measures