Yiheng Liu

Feb 27, 2024 | mdpi.com | Yiheng Liu |Changqing Liu |Ping Liu |Yanqing Xin

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Aug 21, 2023 | mdpi.com | Yiheng Liu |Zhongyu Li |Xianzhi Zhang |Chenqi Cao

2.2. Training ResultPyPEF supports various regression methods, including Random Forest (RF), Support Vector Regression (SVR), Partial Least Squares (PLS), and Multi-Layer Perceptron (MLP) [11]. According to the benchmark of PyPEF, PLS exhibits fast computation speed and high accuracy [11]. Thus, for this study, PLS and MLP were initially selected as the regression methods.