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)

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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

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Apr.19)