Run
10438001

Run 10438001

Task 9964 (Supervised Classification) semeion Uploaded 31-03-2020 by Nicolas Hug
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • openml-python Sklearn_0.23.dev0.
Issue #Downvotes for this reason By


Flow

sklearn.calibration.CalibratedClassifierCV(base_estimator=sklearn.pipeline. Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sk learn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC))(1)Probability calibration with isotonic regression or logistic regression. The calibration is based on the :term:`decision_function` method of the `base_estimator` if it exists, else on :term:`predict_proba`.
sklearn.preprocessing._data.StandardScaler(3)_copytrue
sklearn.preprocessing._data.StandardScaler(3)_with_meantrue
sklearn.preprocessing._data.StandardScaler(3)_with_stdtrue
sklearn.svm._classes.SVC(3)_C1.0
sklearn.svm._classes.SVC(3)_break_tiesfalse
sklearn.svm._classes.SVC(3)_cache_size200
sklearn.svm._classes.SVC(3)_class_weightnull
sklearn.svm._classes.SVC(3)_coef00.0
sklearn.svm._classes.SVC(3)_decision_function_shape"ovr"
sklearn.svm._classes.SVC(3)_degree3
sklearn.svm._classes.SVC(3)_gamma"scale"
sklearn.svm._classes.SVC(3)_kernel"linear"
sklearn.svm._classes.SVC(3)_max_iter-1
sklearn.svm._classes.SVC(3)_probabilityfalse
sklearn.svm._classes.SVC(3)_random_state23438
sklearn.svm._classes.SVC(3)_shrinkingtrue
sklearn.svm._classes.SVC(3)_tol0.001
sklearn.svm._classes.SVC(3)_verbosefalse
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(15)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(15)_copytrue
sklearn.impute._base.SimpleImputer(15)_fill_valuenull
sklearn.impute._base.SimpleImputer(15)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(15)_strategy"mean"
sklearn.impute._base.SimpleImputer(15)_verbose0
sklearn.calibration.CalibratedClassifierCV(base_estimator=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC))(1)_cv5
sklearn.calibration.CalibratedClassifierCV(base_estimator=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC))(1)_method"sigmoid"

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
0.9931 ± 0.0021
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9442 ± 0.0125
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9379 ± 0.014
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.8481 ± 0.0088
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0528 ± 0.002
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18 ± 0
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.9441 ± 0.0126
Cross-validation details (10-fold Crossvalidation)
Number of instances
1593
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9449 ± 0.0123
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9441 ± 0.0126
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3218 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2932 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.126 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4199 ± 0.0209
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.9439 ± 0.0127
Cross-validation details (10-fold Crossvalidation)