LMNNB: Two-in-One imbalanced classification approach by combining metric learning and ensemble learning-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

LMNNB: Two-in-One imbalanced classification approach by combining metric learning and ensemble learning

Published:2021-10-13 Issue: Volume: Page:
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Qiao Shaojie^ORCID,Han Nan,Huang Faliang,Yue Kun,Wu Tao,Yi Yugen,Mao Rui,Yuan Chang-an

Funder

National Natural Science Foundation of China

CCF-Huawei Database System Innovation Research Plan

Sichuan Science and Technology Program

Natural Science Foundation of Guangxi Province

Guangdong Basic and Applied Basic Research Foundation

Guangxi Bagui Teams for Innovation and Research

digital media art, key laboratory of sichuan province, sichuan conservatory of music, chengdu, china

Chengdu Major Science and Technology Innovation Project

Chengdu Technology Innovation and Research and Development Project

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-021-02901-6.pdf

Reference57 articles.

1. Xu S, Yang M, Zhou Yu , Zheng R, Liu W, He J (2020) Partial label metric learning by collapsing classes. Int J Mach Learn Cybern 11(11):2453–2460

2. Ri JH, Tian G, Liu Y, Wei-Hua X, Lou J-G (2020) Extreme learning machine with hybrid cost function of g-mean and probability for imbalance learning. Int J Mach Learn Cybern 11(9):2007–2020

3. Hsiao Y-H, Su C-T, Fu P-C (2020) Integrating MTS with bagging strategy for class imbalance problems. Int J Mach Learn Cybern 11(6):1217–1230

4. Galar M, Fernández A, Tartas EB, Sola HB, Herrera F (2012) A review on ensembles for the class imbalance problem Bagging-boosting-, and hybrid-based approaches. IEEE Trans Syst Man Cybern Part C 42(4):463–484

5. Liu D, Qiao S, Han N, Wu T, Mao R, Zhang Y, Yuan C, Xiao Y (2020) SOTB: Semi-Supervised oversampling approach based on trigonal barycenter theory. IEEE Access 8:50180–50189

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An effective two-stage training scheme for boundary decision of imbalanced samples;International Journal of Machine Learning and Cybernetics;2024-06-14

2. Highly Imbalanced Railway Station Structural Damage Monitoring Based on Cluster-Based Undersampling and Siamese Artificial Neural Network;Arabian Journal for Science and Engineering;2023-09-11

3. LSTMAE-DWSSLM: A unified approach for imbalanced time series data classification;Applied Intelligence;2023-05-10

4. Novel metric-based meta-learning model for few-shot diagnosis of partial discharge in a gas-insulated switchgear;ISA Transactions;2023-03

5. A Comprehensive Survey on Ensemble Learning-Based Intrusion Detection Approaches in Computer Networks;IEEE Access;2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3