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-关于机器学习的最新研究结果已经发表。根据来自爱尔兰戈尔韦的新闻，由NewsRx记者报道，研究称，“为了追求了解地表水质量以促进可持续城市管理，我们创建了一个机器学习利用随机森林(RF)、立体派、极梯度布斯汀(XGB)、多元自适应回归样条(MARS)，梯度提升机(GBM)，支持向量机器(SVM)，以及它们的混合堆叠集成RF(SE-RF)，以及堆叠立体派(SE-Cubist)，西部Howrah市政公司(HMC)区水质分布预测孟加拉，印度。此外，我们采用了ReliefF和Shapley相加解释(SHAP)方法阐明驱动水质的基本因素。
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 tonews originating from Galway, Ireland, by NewsRx correspondents, research stated, “In the pursuit ofunderstanding surface water quality for sustainable urban management, we created a machine learningm odeling framework that utilized Random Forest (RF), Cubist, Extreme Gradient Boo sting (XGB),Multivariate Adaptive Regression Splines (MARS), Gradient Boosting Machine (GBM), Support VectorMachine (SVM), and their hybrid stacking ensemble RF (SE-RF), as well as stacking Cubist (SE-Cubist),to predict the distribution of water quality in the Howrah Municipal Corporation (HMC) area in WestBengal, India. Additionally, we employed the ReliefF and Shapley Additive exPlanations ( SHAP) methodsto elucidate the underlying factors driving water quality.”
NETL
NSTL