首页|Reports on Machine Learning from School of Engineering Provide New Insights (Pre diction of Urban Surface Water Quality Scenarios Using Hybrid Stacking Ensembles Machine Learning Model In Howrah Municipal Corporation, West Bengal)
Reports on Machine Learning from School of Engineering Provide New Insights (Pre diction of Urban Surface Water Quality Scenarios Using Hybrid Stacking Ensembles Machine Learning Model In Howrah Municipal Corporation, West Bengal)
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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.”
GalwayIrelandEuropeCyborgsEmergi ng TechnologiesMachine LearningSchool of Engineering
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