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 language | English |
|---|---|
| Title of host publication | Handbook of pattern recognition and computer vision (2nd ed., pp. 567-578). Singapore: World Scientific Publishing. |
| Editors | C H CHEN , L F PAU , P S P WANG |
| Place of Publication | Singapore |
| Publisher | World Scientific Publishing |
| Pages | 567-578 |
| Edition | 2nd |
| ISBN (Print) | 9810230710 |
| Publication status | Published - 1999 |
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