MSSL: a memetic-based sparse subspace learning algorithm for multi-label classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s13042-022-01616-5.pdf
Reference70 articles.
1. Alzubi OA, Alzubi JA, Alweshah M et al (2020) An optimal pruning algorithm of classifier ensembles: dynamic programming approach. Neural Comput Appl 32:16091–16107. https://doi.org/10.1007/s00521-020-04761-6
2. Bayati H, Dowlatshahi MB, Paniri M (2020a) MLPSO: a filter multi-label feature selection based on particle swarm optimization. In: 2020 25th international computer conference, Computer Society of Iran (CSICC). IEEE, pp 1–6
3. Bayati H, Dowlatshahi MB, Paniri M (2020) Multi-label feature selection based on competitive swarm optimization. J Soft Comput Inf Technol 9:56–69
4. Boutell MR, Luo J, Shen X, Brown CM (2004) Learning multi-label scene classification. Pattern Recognit 37:1757–1771. https://doi.org/10.1016/j.patcog.2004.03.009
5. Cai D, He X, Han J (2007) Spectral regression: a unified approach for sparse subspace learning. In: Proceedings—IEEE international conference on data mining, ICDM. Institute of Electrical and Electronics Engineers Inc., pp 73–82
Cited by 19 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. Boosting Multi-Label Classification Performance Through Meta-Model;International Journal of Pattern Recognition and Artificial Intelligence;2024-01-31
2. Learning shared and non-redundant label-specific features for partial multi-label classification;Information Sciences;2024-01
3. Learning correlation information for multi-label feature selection;Pattern Recognition;2024-01
4. Exploring Ant Colony Optimization for Feature Selection: A Comprehensive Review;Springer Tracts in Nature-Inspired Computing;2024
5. Unsupervised feature selection: A fuzzy multi-criteria decision-making approach;IRAN J FUZZY SYST;2023
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