摘要
机器人与机器学习的新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。据《湖南省新闻报》记者报道，“高吸附容量的‘绿色’生物炭材料的筛选与设计对促进含镉(II)废水的可持续处理起着关键作用，本研究采用了线性回归、Rand OM Forest、梯度提升决策树、cat-Boost、k近邻和backpropagation神经网络六种典型的机器学习(ML)模型。”用该模型预测了生物炭对cd(ii)的吸附容量。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news originating from Hunan, People’s Republ ic of China, by NewsRx correspondents, research stated, “The screening and desig n of ‘green’ biochar materials with high adsorption capacity play a pivotal role in promoting the sustainable treatment of Cd(II)-containing wastewater. In this study, six typical machine learning (ML) models, namely Linear Regression, Rand om Forest, Gradient Boosting Decision Tree, Cat- Boost, K-Nearest Neighbors, and B ackpropagation Neural Network, were employed to accurately predict the adsorptio n capacity of Cd(II) onto biochars.”
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