{"title":"Choice of V for V-fold cross-validation in least-squares density estimation","authors":"ArlotSylvain, LerasleMatthieu","doi":"10.5555/2946645.3053490","DOIUrl":null,"url":null,"abstract":"This paper studies V-fold cross-validation for model selection in least-squares density estimation. The goal is to provide theoretical grounds for choosing V in order to minimize the least-squares ...","PeriodicalId":50161,"journal":{"name":"Journal of Machine Learning Research","volume":"67 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Machine Learning Research","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.5555/2946645.3053490","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper studies V-fold cross-validation for model selection in least-squares density estimation. The goal is to provide theoretical grounds for choosing V in order to minimize the least-squares ...
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