气候变化领域集成服务门户(CCPortal): How to Select an Objective Function Using Information Theory

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DOI	10.1029/2023WR035803
	How to Select an Objective Function Using Information Theory
	Hodson, Timothy O.; Over, Thomas M.; Smith, Tyler J.; Marshall, Lucy M.
发表日期	2024
ISSN	0043-1397
EISSN	1944-7973
起始页码	60
结束页码	5
卷号	60 期号:5
英文摘要	In machine learning or scientific computing, model performance is measured with an objective function. But why choose one objective over another? According to the information-theoretic paradigm, the best objective function is whichever minimizes information loss. To evaluate different objectives, transform them into likelihoods. The ratios of these likelihoods represent how strongly we should prefer one objective versus another, and the log of that ratio represents the relative information loss (or gain) from one objective to another. In plain terms, minimizing information loss is equivalent to minimizing uncertainty, as well as maximizing probability and general utility. We argue that this paradigm is well-suited to models that have many uses and no definite utility like the complex Earth system models used to understand the effects of climate change. Furthermore, the benefits of maximizing information and general utility extend beyond model accuracy to other important considerations including how efficiently the model calibrates, how well it generalizes, and how well it compresses data. A basic problem in modeling is the choice of objective function (or performance metric) According to information theory, the best objective function minimizes information loss, which we evaluate using the AIC Like friction or inefficiency in a system, information loss incurs additional cost however the model is used
英文关键词	model evaluation; objective function; loss function; uncertainty; information theory; probability theory
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
WOS类目	Environmental Sciences ; Limnology ; Water Resources
WOS记录号	WOS:001229535100001
来源期刊	WATER RESOURCES RESEARCH
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/296159
作者单位	United States Department of the Interior; United States Geological Survey; United States Department of the Interior; United States Geological Survey; Clarkson University; Macquarie University
推荐引用方式 GB/T 7714	Hodson, Timothy O.,Over, Thomas M.,Smith, Tyler J.,et al. How to Select an Objective Function Using Information Theory[J],2024,60(5).
APA	Hodson, Timothy O.,Over, Thomas M.,Smith, Tyler J.,&Marshall, Lucy M..(2024).How to Select an Objective Function Using Information Theory.WATER RESOURCES RESEARCH,60(5).
MLA	Hodson, Timothy O.,et al."How to Select an Objective Function Using Information Theory".WATER RESOURCES RESEARCH 60.5(2024).