Run
10394423

Run 10394423

Task 22 (Supervised Classification) mfeat-zernike Uploaded 29-08-2019 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)(2)Automatically created scikit-learn flow.
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(2)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(2)_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)(2)_verbosefalse
sklearn.impute._base.SimpleImputer(3)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(3)_copytrue
sklearn.impute._base.SimpleImputer(3)_fill_valuenull
sklearn.impute._base.SimpleImputer(3)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(3)_strategy"median"
sklearn.impute._base.SimpleImputer(3)_verbose0
sklearn.preprocessing.data.StandardScaler(30)_copytrue
sklearn.preprocessing.data.StandardScaler(30)_with_meantrue
sklearn.preprocessing.data.StandardScaler(30)_with_stdtrue
sklearn.svm.classes.SVC(32)_C2185.5991943304552
sklearn.svm.classes.SVC(32)_cache_size200
sklearn.svm.classes.SVC(32)_class_weightnull
sklearn.svm.classes.SVC(32)_coef00.0
sklearn.svm.classes.SVC(32)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(32)_degree3
sklearn.svm.classes.SVC(32)_gamma0.6661381580873453
sklearn.svm.classes.SVC(32)_kernel"rbf"
sklearn.svm.classes.SVC(32)_max_iter-1
sklearn.svm.classes.SVC(32)_probabilityfalse
sklearn.svm.classes.SVC(32)_random_state1
sklearn.svm.classes.SVC(32)_shrinkingtrue
sklearn.svm.classes.SVC(32)_tol0.001
sklearn.svm.classes.SVC(32)_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
0.6761 ± 0.019
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4455 ± 0.0337
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3522 ± 0.0381
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.3903 ± 0.0358
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1166 ± 0.0069
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6147 ± 0.024
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.417 ± 0.0343
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.417 ± 0.0343
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6478 ± 0.0381
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3415 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.1382 ± 0.0338
Cross-validation details (10-fold Crossvalidation)