• Media type: E-Article
  • Title: Distance classifier ensemble based on intra-class and inter-class scatter
  • Contributor: Guo, Yaqin
  • imprint: EDP Sciences, 2022
  • Published in: E3S Web of Conferences
  • Language: Not determined
  • DOI: 10.1051/e3sconf/202236001041
  • ISSN: 2267-1242
  • Keywords: Pulmonary and Respiratory Medicine ; Pediatrics, Perinatology, and Child Health
  • Origination:
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  • Description: <jats:p>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.</jats:p>
  • Access State: Open Access