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Improving multiclass pattern recognition by the combination of two strategies
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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.