Run
10420109

Run 10420109

Task 53 (Supervised Classification) vehicle Uploaded 03-12-2019 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)_C1913.7930621122962
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef00.2637517935949938
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree1
sklearn.svm.classes.SVC(31)_gamma0.04629480989606259
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.

17 Evaluation measures

0.9495 ± 0.0118
Per class
Cross-validation details (10-fold Crossvalidation)
0.8003 ± 0.0469
Per class
Cross-validation details (10-fold Crossvalidation)
0.7351 ± 0.0625
Cross-validation details (10-fold Crossvalidation)
0.7086 ± 0.0336
Cross-validation details (10-fold Crossvalidation)
0.1403 ± 0.0141
Cross-validation details (10-fold Crossvalidation)
0.3748 ± 0
Cross-validation details (10-fold Crossvalidation)
846
Per class
Cross-validation details (10-fold Crossvalidation)
0.7994 ± 0.0465
Per class
Cross-validation details (10-fold Crossvalidation)
0.8014 ± 0.0469
Cross-validation details (10-fold Crossvalidation)
1.9991 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.8014 ± 0.0469
Per class
Cross-validation details (10-fold Crossvalidation)
0.3744 ± 0.0377
Cross-validation details (10-fold Crossvalidation)
0.4329 ± 0
Cross-validation details (10-fold Crossvalidation)
0.2539 ± 0.0174
Cross-validation details (10-fold Crossvalidation)
0.5864 ± 0.0401
Cross-validation details (10-fold Crossvalidation)