Improving multiclass pattern recognition by the combination of two strategies

Nicolás García-Pedrajas; Domingo Ortiz-Boyer

doi:10.1109/TPAMI.2006.123

Improving multiclass pattern recognition by the combination of two strategies

IEEE Trans Pattern Anal Mach Intell. 2006 Jun;28(6):1001-6. doi: 10.1109/TPAMI.2006.123.

Authors

Nicolás García-Pedrajas¹, Domingo Ortiz-Boyer

Affiliation

¹ Department of Computing and Numerical Analysis, Edificio Einstein, 3a Planta, Campus Universitario de Rabanales, 14071 Córdoba, Spain. npedrajas@uco.es

PMID: 16724593
DOI: 10.1109/TPAMI.2006.123

Abstract

We present a new method of multiclass classification based on the combination of one-vs-all method and a modification of one-vs-one method. This combination of one-vs-all and one-vs-one methods proposed enforces the strength of both methods. A study of the behavior of the two methods identifies some of the sources of their failure. The performance of a classifier can be improved if the two methods are combined in one, in such a way that the main sources of their failure are partially avoided.

Publication types

Comparative Study
Evaluation Study

MeSH terms

Algorithms*
Artificial Intelligence*
Cluster Analysis
Information Storage and Retrieval / methods*
Pattern Recognition, Automated / methods*