Run
10420612

Run 10420612

Task 9957 (Supervised Classification) qsar-biodeg Uploaded 03-12-2019 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)_C1.157552785071378
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.3832400736103765
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree3
sklearn.svm.classes.SVC(31)_gamma0.060575345200107815
sklearn.svm.classes.SVC(31)_kernel"sigmoid"
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

0.8341 ± 0.0383
Per class
Cross-validation details (10-fold Crossvalidation)
0.7849 ± 0.0343
Per class
Cross-validation details (10-fold Crossvalidation)
0.5103 ± 0.0794
Cross-validation details (10-fold Crossvalidation)
0.3727 ± 0.058
Cross-validation details (10-fold Crossvalidation)
0.2839 ± 0.0254
Cross-validation details (10-fold Crossvalidation)
0.4472 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
1055
Per class
Cross-validation details (10-fold Crossvalidation)
0.7855 ± 0.034
Per class
Cross-validation details (10-fold Crossvalidation)
0.7905 ± 0.032
Cross-validation details (10-fold Crossvalidation)
0.9223 ± 0.0036
Cross-validation details (10-fold Crossvalidation)
0.7905 ± 0.032
Per class
Cross-validation details (10-fold Crossvalidation)
0.6347 ± 0.0559
Cross-validation details (10-fold Crossvalidation)
0.4728 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
0.3888 ± 0.0259
Cross-validation details (10-fold Crossvalidation)
0.8222 ± 0.0544
Cross-validation details (10-fold Crossvalidation)