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Distance classifier ensemble based on intra-class and inter-class scatter

E3S Web of Conferences, 2022, Vol.360, p.1041 [Peer Reviewed Journal]

2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2267-1242 ;ISSN: 2555-0403 ;EISSN: 2267-1242 ;DOI: 10.1051/e3sconf/202236001041

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  • Title:
    Distance classifier ensemble based on intra-class and inter-class scatter
  • Author: Guo, Yaqin
  • Long, Y. ; Hou, X. ; Yan, F. ; Li, M.
  • Subjects: Classifiers ; Scattering
  • Is Part Of: E3S Web of Conferences, 2022, Vol.360, p.1041
  • Description: Distance classifier ensemble method based on Intra-class and Inter-class Scatter is proposed in this paper. By Bootstrap technology, the training samples are sampled repeatedly to generate several subsample set, define Intra-class and Inter-class Scatter matrix with subsample set, train subsample set with scatter matrix, generate individual classifier. In the classifier ensemble, the results are integrated with the relative majority voting method. Experiment is tested on UCI standard database, the experimental results show that the proposed ensemble method based on Intra-class and Inter-class Scatter for distance classifier is effective, and it is superior to other methods in classification performance.
  • Publisher: Les Ulis: EDP Sciences
  • Language: English
  • Identifier: ISSN: 2267-1242
    ISSN: 2555-0403
    EISSN: 2267-1242
    DOI: 10.1051/e3sconf/202236001041
  • Source: Open Access: EDP Open
    DOAJ Directory of Open Access Journals
    ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central
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