首页|Study Results from University of Science and Technology Beijing Update Understan ding of Machine Learning (Viscosity and Melting Temperature Prediction of Mold F luxes Based On Explainable Machine Learning and Shapley Additive Explanations)
Study Results from University of Science and Technology Beijing Update Understan ding of Machine Learning (Viscosity and Melting Temperature Prediction of Mold F luxes Based On Explainable Machine Learning and Shapley Additive Explanations)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Viscosity and melting temperature are indispensable properties for mold flux design and evaluation, significant i nvestment is required for measurement. In this paper, viscosity and melting temp erature predictive model for mold fluxes were established and trained based on 3 300 groups of data and four representative machine learning algorithms.”
NETL
NSTL
