Model performance results based on random forest, gradient boosting, penalized logistic regression, XGBoost, SVM, neural network, and stacking for APAT data as training set and EMBARC data as testing set after multiple imputation for 10 times.
收藏Figshare2024-03-28 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Model_performance_results_based_on_random_forest_gradient_boosting_penalized_logistic_regression_XGBoost_SVM_neural_network_and_stacking_for_APAT_data_as_training_set_and_EMBARC_data_as_testing_set_after_multiple_imputation_for_10_times_/25501665
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资源简介：
Model performance results based on random forest, gradient boosting, penalized logistic regression, XGBoost, SVM, neural network, and stacking for APAT data as training set and EMBARC data as testing set after multiple imputation for 10 times.
创建时间：
2024-03-28
