If callable, a custom evaluation metric. The call signature is func(y_predicted, y_true) where y_true will be a DMatrix object such that you may need to call the get_label method. It must return a str, value pair where the str is a name for the evaluation and value is the value ...
(cv_model)#> Summary for CrossValidatorModel#> <cross_validator__13c346ec_bc09_4b8a_952d_92f9711299d7>#>#> Tuned Pipeline#> with metric f1#> over 4 hyperparameter sets#> via 3-fold cross validation#>#> Estimator: Pipeline#> <pipeline__bf0a05c1_6f0e_4875_ac1a_c77fbd6635f3>#...
loss_function='MultiClass', custom_metric=['AUC'], eval_metric='MultiClass', random_seed=1996) cat_boost_model.fit(X_train, y_train, eval_set=(X_test, y_test), use_best_model=True, early_stopping_rounds=1000) y_pred = cat_boost_model.predict(X_test) cat_acc = accuracy_score(y...
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