Run
10424930

Run 10424930

Task 3902 (Supervised Classification) pc4 Uploaded 05-12-2019 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"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)_C24.914879698244018
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.4493437243447289
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree1
sklearn.svm.classes.SVC(31)_gamma0.09788693771469986
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

Area under ROC curve
0.906 ± 0.0404
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8993 ± 0.0152
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4742 ± 0.0777
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.2682 ± 0.0627
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1372 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2148 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.9143 ± 0.0121
Cross-validation details (10-fold Crossvalidation)
Number of instances
1458
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9086 ± 0.019
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9143 ± 0.0121
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5353 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6391 ± 0.0439
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3274 ± 0.003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2567 ± 0.0163
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7842 ± 0.0479
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.6803 ± 0.0361
Cross-validation details (10-fold Crossvalidation)