摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的最新研究结果已经发表。据新闻报道由NewsRx记者从意大利罗马发回的报道称，“本研究提出了一项新的研究。”基于自然梯度提升(NGBoost)的概率机器学习(ML)预测方法钢管混凝土(CFST)柱轴压承载力。利用全面的本文对1127个钢管混凝土轴心受压试件的试验数据进行了比较各种ML算法的性能"。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting originating from Rome, Ital y, by NewsRx correspondents, research stated, “This study presents anovel proba bilistic machine learning (ML) approach using Natural Gradient Boosting (NGBoost ) to predictthe axial compressive capacity of Concrete Filled Steel Tube (CFST) columns. Leveraging a comprehensivedataset of 1,127 experimentally tested CFST specimens under axial compressive loads, we compare theperformance of various ML algorithms.”
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