随着工业化和城市化的快速发展,水质安全问题日益受到关注.本研究利用一个包含7999条数据记录的水质分析数据集,涵盖多种化学物质浓度测量值与安全阈值,以及"是否安全"分类变量,运用Extra Tree Classifier模型进行水质安全建模预测及数据分析.本研究目的在于提供一个可靠的模型,以帮助决策者和相关部门更好地监测和维护水质安全,从而保障公众健康和环境可持续发展.
Water Quality Safety Modeling Prediction Based on Extra Tree Classifier
With the rapid development of industrialization and urbanization,water quality safety issues have attracted increasing attention.This study uses a water quality analysis data set containing 7999 data records,covering various chemical substance concentration measurements and safety thresholds,as well as"safe or not"classification variables,and uses the Extra Tree Classifier model to conduct water quality safety modeling prediction and data analysis.The purpose of this study is to provide a reliable model to help policymakers and relevant departments better monitor and maintain water quality safety,thereby ensuring public health and environmental sustainability.
water quality safetyLazy PredictExtra Tree ClassifierK-fold cross validationmachine learning
杨丽佳、陈新房、赵晗清、汪世伟
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防灾科技学院,河北三河 065201
河北省高校智慧应急应用技术研发中心,河北三河 065201
水质安全 Lazy Predict Extra Tree Classifier k折交叉验证 机器学习
NETL
NSTL
万方数据
