Run
10438088

Run 10438088

Task 3481 (Supervised Classification) isolet Uploaded 31-03-2020 by Nicolas Hug
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  • openml-python Sklearn_0.23.dev0.
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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_state40393
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

0.9985 ± 0.0007
Per class
Cross-validation details (10-fold Crossvalidation)
0.9684 ± 0.0059
Per class
Cross-validation details (10-fold Crossvalidation)
0.9672 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
0.898 ± 0.0033
Cross-validation details (10-fold Crossvalidation)
0.0204 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.074 ± 0
Cross-validation details (10-fold Crossvalidation)
0.9684 ± 0.006
Cross-validation details (10-fold Crossvalidation)
7797
Per class
Cross-validation details (10-fold Crossvalidation)
0.9685 ± 0.006
Per class
Cross-validation details (10-fold Crossvalidation)
0.9684 ± 0.006
Cross-validation details (10-fold Crossvalidation)
4.7004 ± 0
Cross-validation details (10-fold Crossvalidation)
0.2755 ± 0.0036
Cross-validation details (10-fold Crossvalidation)
0.1923 ± 0
Cross-validation details (10-fold Crossvalidation)
0.0743 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.3864 ± 0.0097
Cross-validation details (10-fold Crossvalidation)
0.9684 ± 0.0059
Cross-validation details (10-fold Crossvalidation)