A feature selection method based on multiple feature subsets extraction and result fusion for improving classification performance-Reference-Cited by-同舟云学术

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A feature selection method based on multiple feature subsets extraction and result fusion for improving classification performance

Published:2024-01 Issue: Volume:150 Page:111018
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Liu Jia,Li Dong^ORCID,Shan Wangweiyi,Liu Shulin

Publisher

Elsevier BV

Subject

Software

Reference39 articles.

1. Feature selection: a data perspective;Li;ACM Comput. Surv. (CSUR),2017

2. Nonlinear industrial process fault diagnosis with latent label consistency and sparse Gaussian feature learning;Li;J. Cent. South Univ.,2022

3. Deep branch attention network and extreme multi-scale entropy based single vibration signal-driven variable speed fault diagnosis scheme for rolling bearing;Zhao;Adv. Eng. Inform.,2023

4. Feature unionization: a novel approach for dimension reduction;Jalilvand;Appl. Soft Comput.,2017

5. Udrn: unified dimensional reduction neural network for feature selection and feature projection;Zang;Neural Netw.,2023

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