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31811

Run 31811

Task 119 (Supervised Classification) diabetes Uploaded 30-03-2021 by Continuous Integration
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TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklear n.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.S VC))(1)Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "predict", "predict_proba", "decision_function", "transform" and "inverse_transform" if they are implemented in the estimator used. The parameters of the estimator used to apply these methods are optimized by cross-validated grid-search over a parameter grid.
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_cv3
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_error_scoreNaN
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_iid"deprecated"
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_n_jobsnull
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_param_grid{"base_estimator__C": [0.01, 0.1, 10], "base_estimator__gamma": [0.01, 0.1, 10]}
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_pre_dispatch"2*n_jobs"
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_refittrue
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_return_train_scorefalse
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_scoringnull
TESTfc5c23eb1fsklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_verbose0
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_bootstraptrue
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_bootstrap_featuresfalse
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_max_features1.0
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_max_samples1.0
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_n_estimators10
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_n_jobsnull
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_oob_scorefalse
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_random_state33003
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_verbose0
TESTfc5c23eb1fsklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_warm_startfalse
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_C1.0
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_break_tiesfalse
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_cache_size200
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_class_weightnull
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_coef00.0
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_decision_function_shape"ovr"
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_degree3
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_gamma"scale"
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_kernel"rbf"
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_max_iter-1
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_probabilityfalse
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_random_state62501
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_shrinkingtrue
TESTfc5c23eb1fsklearn.svm._classes.SVC(1)_tol0.001
TESTfc5c23eb1fsklearn.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.

arff
Trace

ARFF file with the trace of all hyperparameter settings tried during optimization, and their performance.

18 Evaluation measures

0.5627
Per class
Cross-validation details (10% Holdout set)
0.5737
Per class
Cross-validation details (10% Holdout set)
0.0944
Cross-validation details (10% Holdout set)
0.2054
Cross-validation details (10% Holdout set)
0.3518
Cross-validation details (10% Holdout set)
0.4589
Cross-validation details (10% Holdout set)
0.6482
Cross-validation details (10% Holdout set)
253
Per class
Cross-validation details (10% Holdout set)
0.6233
Per class
Cross-validation details (10% Holdout set)
0.6482
Cross-validation details (10% Holdout set)
0.9463
Cross-validation details (10% Holdout set)
0.7665
Cross-validation details (10% Holdout set)
0.4813
Cross-validation details (10% Holdout set)
0.5705
Cross-validation details (10% Holdout set)
1.1854
Cross-validation details (10% Holdout set)
0.5396
Cross-validation details (10% Holdout set)