Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 유재근 | * |
dc.date.accessioned | 2019-10-02T02:00:04Z | - |
dc.date.available | 2019-10-02T02:00:04Z | - |
dc.date.issued | 2019 | * |
dc.identifier.issn | 0169-7439 | * |
dc.identifier.other | OAK-25373 | * |
dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/251507 | - |
dc.description.abstract | High-dimensional data analysis often suffers the so-called curse of dimensionality, and various data reduction methods are adopted in order to avoid it in practice. Consequently, in multivariate regression, high-dimensional predictors should be reduced to lower-dimensional ones without the loss of information, following a notion of sufficient dimension reduction. In this paper, a fused clustered seeded reduction approach is proposed for multivariate regression. The proposed method utilizes two types of information: supervised learning between the responses and the predictors, and unsupervised learning of the predictors alone. Fusing all the information has a potential advantage in the accuracy of the reduction of predictors. Numerical studies and a real data analysis confirm the practical usefulness of the proposed approach over existing methods. © 2019 Elsevier B.V. | * |
dc.language | English | * |
dc.publisher | Elsevier B.V. | * |
dc.subject | Fused approach | * |
dc.subject | K-means clustering | * |
dc.subject | Large p small n | * |
dc.subject | Multivariate analysis | * |
dc.subject | Seeded reduction | * |
dc.title | On fused dimension reduction in multivariate regression | * |
dc.type | Article | * |
dc.relation.volume | 193 | * |
dc.relation.index | SCIE | * |
dc.relation.index | SCOPUS | * |
dc.relation.journaltitle | Chemometrics and Intelligent Laboratory Systems | * |
dc.identifier.doi | 10.1016/j.chemolab.2019.103828 | * |
dc.identifier.wosid | WOS:000491639400006 | * |
dc.identifier.scopusid | 2-s2.0-85071579941 | * |
dc.author.google | Lee K. | * |
dc.author.google | Choi Y. | * |
dc.author.google | Um H.Y. | * |
dc.author.google | Yoo J.K. | * |
dc.contributor.scopusid | 유재근(23032759600) | * |
dc.date.modifydate | 20240130113500 | * |