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了解弗林特住宅水污染的数据科学方法

A Data Science Approach to Understanding Residential Water Contamination in Flint
课程网址: http://videolectures.net/kdd2017_webb_water_contamination/  
主讲教师: Jared Webb
开课单位: 杨百翰大学
开课时间: 2017-10-09
课程语种: 英语
中文简介:
当弗林特的居民得知铅污染了他们的供水系统时,当地政府向他们免费提供水质检测套件。市政府公布了这些测试的结果,创建了一个有价值的数据集,对于了解弗林特铅污染事件的原因和程度至关重要。这是全国最大的市政供水系统铅数据集。在本文中,我们预测了每个家庭供水的铅污染情况,并研究了弗林特水问题的几个相关方面,其中许多问题远远超出了这座城市的范围。例如,我们表明可以通过可观察的家庭属性(弱地)预测铅风险升高。然后我们探讨与铅升高相关的因素。这些风险评估部分是通过密歇根大学的众包预测挑战赛开发的。为了向弗林特居民通报这些评估,它们已被纳入由 \texttt{Google.org} 资助的网络和移动应用程序中。我们还探讨了住宅测试计划中的自我选择问题,检查哪些因素与居民自愿采样水的时间和频率相关。
课程简介: When the residents of Flint learned that lead had contaminated their water system, the local government made water-testing kits available to them free of charge. The city government published the results of these tests, creating a valuable dataset that is key to understanding the causes and extent of the lead contamination event in Flint. This is the nation's largest dataset on lead in a municipal water system. In this paper, we predict the lead contamination for each household's water supply, and we study several related aspects of Flint's water troubles, many of which generalize well beyond this one city. For example, we show that elevated lead risks can be (weakly) predicted from observable home attributes. Then we explore the factors associated with elevated lead. These risk assessments were developed in part via a crowd sourced prediction challenge at the University of Michigan. To inform Flint residents of these assessments, they have been incorporated into a web and mobile application funded by texttt{Google.org}. We also explore questions of self-selection in the residential testing program, examining which factors are linked to when and how frequently residents voluntarily sample their water.
关 键 词: 数据科学; 数据集; 水污染
课程来源: 视频讲座网
数据采集: 2023-12-25:wujk
最后编审: 2024-01-22:liyy
阅读次数: 16