Run
8983

Run 8983

Task 119 (Supervised Classification) diabetes Uploaded 01-02-2024 by Continuous Integration
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TEST8e04664260sklearn.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.
TEST8e04664260sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_cv3
TEST8e04664260sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_error_scoreNaN
TEST8e04664260sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_iid"deprecated"
TEST8e04664260sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_n_jobsnull
TEST8e04664260sklearn.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]}
TEST8e04664260sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_pre_dispatch"2*n_jobs"
TEST8e04664260sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_refittrue
TEST8e04664260sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_return_train_scorefalse
TEST8e04664260sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_scoringnull
TEST8e04664260sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC))(1)_verbose0
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_bootstraptrue
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_bootstrap_featuresfalse
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_max_features1.0
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_max_samples1.0
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_n_estimators10
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_n_jobsnull
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_oob_scorefalse
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_random_state33003
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_verbose0
TEST8e04664260sklearn.ensemble._bagging.BaggingClassifier(base_estimator=sklearn.svm._classes.SVC)(1)_warm_startfalse
TEST8e04664260sklearn.svm._classes.SVC(1)_C1.0
TEST8e04664260sklearn.svm._classes.SVC(1)_break_tiesfalse
TEST8e04664260sklearn.svm._classes.SVC(1)_cache_size200
TEST8e04664260sklearn.svm._classes.SVC(1)_class_weightnull
TEST8e04664260sklearn.svm._classes.SVC(1)_coef00.0
TEST8e04664260sklearn.svm._classes.SVC(1)_decision_function_shape"ovr"
TEST8e04664260sklearn.svm._classes.SVC(1)_degree3
TEST8e04664260sklearn.svm._classes.SVC(1)_gamma"scale"
TEST8e04664260sklearn.svm._classes.SVC(1)_kernel"rbf"
TEST8e04664260sklearn.svm._classes.SVC(1)_max_iter-1
TEST8e04664260sklearn.svm._classes.SVC(1)_probabilityfalse
TEST8e04664260sklearn.svm._classes.SVC(1)_random_state62501
TEST8e04664260sklearn.svm._classes.SVC(1)_shrinkingtrue
TEST8e04664260sklearn.svm._classes.SVC(1)_tol0.001
TEST8e04664260sklearn.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

Area under ROC curve
0.5627
Per class
F measure
0.5737
Per class
Kappa
0.0944
KB relative information score
0.2054
Mean absolute error
0.3518
Mean prior absolute error
0.4589
Weighted recall
0.6482
Number of instances
253
Per class
Precision
0.6233
Per class
Predictive accuracy
0.6482
Prior entropy
0.9463
Relative absolute error
0.7665
Root mean prior squared error
0.4813
Root mean squared error
0.5705
Root relative squared error
1.1854
Unweighted recall
0.5396