首页|Study Findings from Northeastern University Provide New Insights into Machine Le arning (Interpretable Predictive Model for Inclusions In Electroslag Remelting B ased On Xgboost and Shap Analysis)
Study Findings from Northeastern University Provide New Insights into Machine Le arning (Interpretable Predictive Model for Inclusions In Electroslag Remelting B ased On Xgboost and Shap Analysis)
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 DailyNews Daily News – Researchers detail new data in Machine Learning. According to news reporting originatingfrom Shenyang, People’s Repub lic of China, by NewsRx correspondents, research stated, “The useof machine lea rning techniques in the metallurgical field has been gradually expanding, but it s applicationin the area of electroslag remelting (ESR) is limited, and the und erlying predictive processes of currentmachine learning models lack exploration . In this study, a predictive method based on SHAP theory andXGBoost algorithm is proposed to forecast B-type inclusions in the process of ESR.”
ShenyangPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningNortheastern University