Classification of human chromosomes: A study of correlated behavior in majority vote

Suk Wah Louisa LAM, Ching Y. SUEN

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Methods for combining multiple classifiers have been developed for improved performance in pattern recognition. This paper examines nine correlated classifiers from the perspective of majority voting. It demonstrates that relationships between the classifiers can be observed from the voting results, that the error reduction ability of a combination varies inversely with the correlation among the classifiers to be combined, and that the correlation coefficient is an effective measure for selecting a subset of classifiers for combination to achieve the best results. Copyright © 1999 World Scientific Publishing.
Original languageEnglish
Title of host publicationHandbook of pattern recognition and computer vision (2nd ed., pp. 567-578). Singapore: World Scientific Publishing.
EditorsC H CHEN , L F PAU , P S P WANG
Place of PublicationSingapore
PublisherWorld Scientific Publishing
Pages567-578
Edition2nd
ISBN (Print)9810230710
Publication statusPublished - 1999

Fingerprint

Chromosomes
Classifiers
Pattern recognition

Citation

Lam, L., & Suen, C. Y. (1999). Classification of human chromosomes: A study of correlated behavior in majority vote. In C. H. Chen, L. F. Pau, & P. S. P. Wang (Eds.), Handbook of pattern recognition and computer vision (2nd ed., pp. 567-578). Singapore: World Scientific Publishing.

Keywords

  • Classification of chromosomes
  • Majority vote
  • Combination of classifiers