OpenML
10343165

Run 10343165

Task 3917 (Supervised Classification) kc1 Uploaded 21-08-2019 by Heinrich Peters
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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"most_frequent"
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)_C3.081620245614723
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.053322514098660845
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree5
sklearn.svm.classes.SVC(31)_gamma0.31447231452702795
sklearn.svm.classes.SVC(31)_kernel"poly"
sklearn.svm.classes.SVC(31)_max_iter-1
sklearn.svm.classes.SVC(31)_probabilityfalse
sklearn.svm.classes.SVC(31)_random_state43276
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.

17 Evaluation measures

Area under ROC curve
0.5646 ± 0.038
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7772 ± 0.0238
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1336 ± 0.0783
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-0.0345 ± 0.1319
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2191 ± 0.0283
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2616 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
Number of instances
2109
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7736 ± 0.0205
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7809 ± 0.0283
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.6212 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
Recall
0.7809 ± 0.0283
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8374 ± 0.1071
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3615 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.468 ± 0.0294
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2947 ± 0.0806
Cross-validation details (10-fold Crossvalidation)