Ying-Chang Li

3.4. Evaluation of Model Using Testing Set To ensure the reliability and generalizability of the SVM classifier’s performance, k-fold cross-validation was employed during the model evaluation process. In k-fold cross-validation, the dataset is divided into k equally sized folds. The model is then trained on k-1 folds and tested on the remaining fold. This process is repeated k times, with each fold being used as the test set exactly once.

Open AccessArticle by Ming-Jer Jeng 1,2, Ying-Chang Li 3, Mukta Sharma 1, Chia-Wei Chen 1, Chia-Lung Tsai 1,2,*, Yen-Heng Lin 1, Shiang-Fu Huang 2,4,*, Liann-Be Chang 1,2 and Chao-Sung Lai 1 1 Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan 2 Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan 3 Green Technology Research Center, Chang Gung University, Taoyuan 333, Taiwan 4 Department of Public Health, Chang Gung...