Beyond prediction: Using big data for policy problems

GSTDTAP > 地球科学

DOI	10.1126/science.aal4321
	Beyond prediction: Using big data for policy problems
	Athey, Susan
	2017-02-03
发表期刊	SCIENCE
ISSN	0036-8075
EISSN	1095-9203
出版年	2017
卷号	355 期号:6324 页码:483-485
文章类型	Editorial Material
语种	英语
国家	USA
英文摘要	Machine-learning prediction methods have been extremely productive in applications ranging from medicine to allocating fire and health inspectors in cities. However, there are a number of gaps between making a prediction and making a decision, and underlying assumptions need to be understood in order to optimize data-driven decision-making.
领域	地球科学 ; 气候变化 ; 资源环境
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000393183100034
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
URL	查看原文
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/195346
专题	地球科学资源环境科学气候变化
作者单位	Stanford Univ, Grad Sch Business, Stanford, CA 94305 USA
推荐引用方式 GB/T 7714	Athey, Susan. Beyond prediction: Using big data for policy problems[J]. SCIENCE,2017,355(6324):483-485.
APA	Athey, Susan.(2017).Beyond prediction: Using big data for policy problems.SCIENCE,355(6324),483-485.
MLA	Athey, Susan."Beyond prediction: Using big data for policy problems".SCIENCE 355.6324(2017):483-485.