Home>Results

  • Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
成果搜索

[期刊论文]

Sparse group feature selection by weighted thresholding homotopy method

Share
Edit Delete 报错

author:

Wu, J. (Wu, J..) [1] | Huang, H. (Huang, H..) [2] | Zhu, W. (Zhu, W..) [3]

Indexed by:

Scopus

Abstract:

In this paper, we investigate the sparse group feature selection problem, in which covariates posses a grouping structure sparsity at the level of both features and groups simultaneously. We reformulate the feature sparsity constraint as an equivalent weighted l1-norm constraint in the sparse group optimization problem. To solve the reformulated problem, we first propose a weighted thresholding method based on a dynamic programming algorithm. Then we improve the method to a weighted thresholding homotopy algorithm using homotopy technique. We prove that the algorithm converges to an L-stationary point of the original problem. Computational experiments on synthetic data show that the proposed algorithm is competitive with some state-of-the-art algorithms. © 2013 IEEE.

Keyword:

Homotopy technique; sparse group feature selection; weighted thresholding method

Community:

  • [ 1 ] [Wu, J.]College of Computer and Control Engineering, Minjiang University, Fuzhou, 350116, China
  • [ 2 ] [Huang, H.]Center for Discrete Mathematics and Theoretical Computer Science, Fuzhou University, Fuzhou, 350116, China
  • [ 3 ] [Zhu, W.]Center for Discrete Mathematics and Theoretical Computer Science, Fuzhou University, Fuzhou, 350116, China

Reprint 's Address:

  • [Zhu, W.]Center for Discrete Mathematics and Theoretical Computer Science, Fuzhou UniversityChina

Show more details

Source :

IEEE Access

ISSN: 2169-3536

Year: 2020

Volume: 8

Page: 20700-20707

3 . 3 6 7

JCR@2020

3 . 4 0 0

JCR@2023

ESI HC Threshold:132

JCR Journal Grade:2

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

30 Days PV: 1

Affiliated Colleges:

操作日志

管理员  2025-02-13 03:26:03  更新被引

管理员  2025-02-13 00:39:26  更新被引

管理员  2020-11-19 20:30:00  创建

Online/Total:34/10460187
Address:FZU Library(No.2 Xuyuan Road, Fuzhou, Fujian, PRC Post Code:350116) Contact Us:0591-22865326
Copyright:FZU Library Technical Support:Beijing Aegean Software Co., Ltd. 闽ICP备05005463号-1