A comparative study of feature screening methods for ultrahigh dimensional multiclass classification
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Kyungeun | - |
dc.contributor.author | Kim, Kyoung Hee | - |
dc.contributor.author | Shin, Seung Jun | - |
dc.date.accessioned | 2021-09-03T00:24:20Z | - |
dc.date.available | 2021-09-03T00:24:20Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2017-10 | - |
dc.identifier.issn | 1225-066X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/82017 | - |
dc.description.abstract | We compare various variable screening methods on multiclass classification problems when the data is ultrahigh-dimensional. Two different approaches were considered: (1) pairwise extension from binary classification via one versus one or one versus rest comparisons and (2) direct classification of multiclass responses. We conducted extensive simulation studies under different conditions: heavy tailed explanatory variables, correlated signal and noise variables, correlated joint distributions but uncorrelated marginals, and unbalanced response variables. We then analyzed real data to examine the performance of the methods. The results showed that model-free methods perform better for multiclass classification problems as well as binary ones. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | KOREAN STATISTICAL SOC | - |
dc.subject | FEATURE-SELECTION | - |
dc.subject | MODEL | - |
dc.subject | REGRESSION | - |
dc.title | A comparative study of feature screening methods for ultrahigh dimensional multiclass classification | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Shin, Seung Jun | - |
dc.identifier.doi | 10.5351/KJAS.2017.30.5.793 | - |
dc.identifier.wosid | 000424587600013 | - |
dc.identifier.bibliographicCitation | KOREAN JOURNAL OF APPLIED STATISTICS, v.30, no.5, pp.793 - 808 | - |
dc.relation.isPartOf | KOREAN JOURNAL OF APPLIED STATISTICS | - |
dc.citation.title | KOREAN JOURNAL OF APPLIED STATISTICS | - |
dc.citation.volume | 30 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 793 | - |
dc.citation.endPage | 808 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002281357 | - |
dc.description.journalClass | 2 | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | FEATURE-SELECTION | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordPlus | REGRESSION | - |
dc.subject.keywordAuthor | multi-categorical classification | - |
dc.subject.keywordAuthor | simulation | - |
dc.subject.keywordAuthor | ultrahigh-dimensional classification | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.