Run
10397913

Run 10397913

Task 49 (Supervised Classification) tic-tac-toe Uploaded 02-09-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm .classes.SVC)(2)Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(3)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(3)_copytrue
sklearn.impute._base.SimpleImputer(3)_fill_valuenull
sklearn.impute._base.SimpleImputer(3)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(3)_strategy"most_frequent"
sklearn.impute._base.SimpleImputer(3)_verbose0
sklearn.svm.classes.SVC(32)_C0.42681252219264904
sklearn.svm.classes.SVC(32)_cache_size200
sklearn.svm.classes.SVC(32)_class_weightnull
sklearn.svm.classes.SVC(32)_coef00.23495235580748663
sklearn.svm.classes.SVC(32)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(32)_degree4
sklearn.svm.classes.SVC(32)_gamma0.0419665675168468
sklearn.svm.classes.SVC(32)_kernel"rbf"
sklearn.svm.classes.SVC(32)_max_iter-1
sklearn.svm.classes.SVC(32)_probabilityfalse
sklearn.svm.classes.SVC(32)_random_state1
sklearn.svm.classes.SVC(32)_shrinkingtrue
sklearn.svm.classes.SVC(32)_tol0.001
sklearn.svm.classes.SVC(32)_verbosefalse
sklearn.preprocessing._encoders.OneHotEncoder(12)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_dropnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(12)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(12)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_sparsetrue
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm.classes.SVC)(2)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm.classes.SVC)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm.classes.SVC)(2)_verbosefalse

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

0.7254 ± 0.0455
Per class
Cross-validation details (10-fold Crossvalidation)
0.7829 ± 0.0413
Per class
Cross-validation details (10-fold Crossvalidation)
0.5099 ± 0.0908
Cross-validation details (10-fold Crossvalidation)
0.5485 ± 0.0732
Cross-validation details (10-fold Crossvalidation)
0.1962 ± 0.0319
Cross-validation details (10-fold Crossvalidation)
0.453 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
958
Per class
Cross-validation details (10-fold Crossvalidation)
0.8297 ± 0.025
Per class
Cross-validation details (10-fold Crossvalidation)
0.8038 ± 0.0319
Cross-validation details (10-fold Crossvalidation)
0.931 ± 0.0039
Cross-validation details (10-fold Crossvalidation)
0.8038 ± 0.0319
Per class
Cross-validation details (10-fold Crossvalidation)
0.4332 ± 0.0703
Cross-validation details (10-fold Crossvalidation)
0.4759 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
0.443 ± 0.0364
Cross-validation details (10-fold Crossvalidation)
0.9309 ± 0.0765
Cross-validation details (10-fold Crossvalidation)