摘要
由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-调查人员讨论机器学习的新发现。根据NewsRx编辑来自浙江的新闻报道，该研究表明：“利用机器学习(ML)工具对废旧材料制备的可持续砂浆的抗压强度(CS)和抗折强度(FS)进行了测试，并利用Ex treme梯度提升(XGB)和Bagging回归器(BR)等集成ML技术实现了研究目标。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting originating from Zhejiang, People’ s Republic of China, by NewsRx editors, the research stated, “Compressive (CS) a nd flexural strength (FS) of sustainable mortar made from waste materials were e stimated using machine learning (ML) tools. Ensemble ML techniques, including ex treme gradient boosting (XGB) and bagging regressor (BR), were utilized to accom plish the study goals.”
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