Run
10434508

Run 10434508

Task 167119 (Supervised Classification) jungle_chess_2pcs_raw_endgame_complete Uploaded 18-12-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.cl asses.SVC)(1)Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(1)_copytrue
sklearn.impute._base.SimpleImputer(1)_fill_valuenull
sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(1)_strategy"median"
sklearn.impute._base.SimpleImputer(1)_verbose0
sklearn.preprocessing.data.StandardScaler(29)_copytrue
sklearn.preprocessing.data.StandardScaler(29)_with_meantrue
sklearn.preprocessing.data.StandardScaler(29)_with_stdtrue
sklearn.svm.classes.SVC(31)_C0.6924057373577415
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef00.46594279667222027
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree2
sklearn.svm.classes.SVC(31)_gamma0.027501589087229522
sklearn.svm.classes.SVC(31)_kernel"poly"
sklearn.svm.classes.SVC(31)_max_iter-1
sklearn.svm.classes.SVC(31)_probabilitytrue
sklearn.svm.classes.SVC(31)_random_state1
sklearn.svm.classes.SVC(31)_shrinkingtrue
sklearn.svm.classes.SVC(31)_tol0.001
sklearn.svm.classes.SVC(31)_verbosefalse
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_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.

18 Evaluation measures

0.8867 ± 0.0044
Per class
Cross-validation details (10-fold Crossvalidation)
0.7539 ± 0.0072
Per class
Cross-validation details (10-fold Crossvalidation)
0.5822 ± 0.012
Cross-validation details (10-fold Crossvalidation)
0.4633 ± 0.0064
Cross-validation details (10-fold Crossvalidation)
0.2276 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
0.3832 ± 0
Cross-validation details (10-fold Crossvalidation)
0.7688 ± 0.0064
Cross-validation details (10-fold Crossvalidation)
44819
Per class
Cross-validation details (10-fold Crossvalidation)
0.7497 ± 0.0078
Per class
Cross-validation details (10-fold Crossvalidation)
0.7688 ± 0.0064
Cross-validation details (10-fold Crossvalidation)
1.3491 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.5941 ± 0.0059
Cross-validation details (10-fold Crossvalidation)
0.4377 ± 0
Cross-validation details (10-fold Crossvalidation)
0.334 ± 0.0028
Cross-validation details (10-fold Crossvalidation)
0.7631 ± 0.0064
Cross-validation details (10-fold Crossvalidation)
0.6144 ± 0.01
Cross-validation details (10-fold Crossvalidation)