Run
10435455

Run 10435455

Task 3904 (Supervised Classification) jm1 Uploaded 03-01-2020 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)_C16243.68103733974
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.8809338361698618
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree4
sklearn.svm.classes.SVC(31)_gamma0.021173334999499905
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
0.653 ± 0.017
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7206 ± 0.0007
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0015 ± 0.0032
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0019 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3115 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3121 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.8067 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Number of instances
10885
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8441 ± 0.0003
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8067 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7087 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9982 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.395 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3949 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9997 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.5005 ± 0.001
Cross-validation details (10-fold Crossvalidation)