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Improving multiclass pattern recognition by the combination of two strategies

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2 Author(s)
N. Garcia-Pedrajas ; Dept. of Comput. & Numerical Anal., Campus Univ. de Rabanales, Cordoba, Spain ; D. Ortiz-Boyer

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.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:28 ,  Issue: 6 )