Author: Jiangpeng Wu; Pengyi Zhang; Liting Zhang; Wenbo Meng; Junfeng Li; Chongxiang Tong; Yonghong Li; Jing Cai; Zengwei Yang; Jinhong Zhu; Meie Zhao; Huirong Huang; Xiaodong Xie; Shuyan Li
Title: Rapid and accurate identification of COVID-19 infection through machine learning based on clinical available blood test results Document date: 2020_4_6
ID: kjovtgua_12
Snippet: Firstly, the internal 10-fold cross-validation which was performed on the training set was a persuasive and universal method to obtain robust performance. Secondly, the test set is totally different from the training set just to verify the discriminating ability of the tool. In addition, all modeling processes were accomplished in the training set based on 10-fold cross-validation and had no connection to the test set......
Document: Firstly, the internal 10-fold cross-validation which was performed on the training set was a persuasive and universal method to obtain robust performance. Secondly, the test set is totally different from the training set just to verify the discriminating ability of the tool. In addition, all modeling processes were accomplished in the training set based on 10-fold cross-validation and had no connection to the test set.
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