Improving multiclass pattern recognition by the combination of two strategies.
other · Level V
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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.
Medical subject headings
- Algorithms
- Artificial Intelligence
- Information Storage and Retrieval
- Pattern Recognition, Automated