{"title":"规则增强惩罚回归","authors":"Jonathan Eckstein, Ai Kagawa, Noam Goldberg","doi":"10.1287/IJOO.2019.0015","DOIUrl":null,"url":null,"abstract":"This article describes a new rule-enhanced penalized regression procedure for the generalized regression problem of predicting scalar responses from observation vectors in the absence of a preferre...","PeriodicalId":73382,"journal":{"name":"INFORMS journal on optimization","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1287/IJOO.2019.0015","citationCount":"10","resultStr":"{\"title\":\"REPR: Rule-Enhanced Penalized Regression\",\"authors\":\"Jonathan Eckstein, Ai Kagawa, Noam Goldberg\",\"doi\":\"10.1287/IJOO.2019.0015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article describes a new rule-enhanced penalized regression procedure for the generalized regression problem of predicting scalar responses from observation vectors in the absence of a preferre...\",\"PeriodicalId\":73382,\"journal\":{\"name\":\"INFORMS journal on optimization\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1287/IJOO.2019.0015\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"INFORMS journal on optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1287/IJOO.2019.0015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"INFORMS journal on optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/IJOO.2019.0015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This article describes a new rule-enhanced penalized regression procedure for the generalized regression problem of predicting scalar responses from observation vectors in the absence of a preferre...