Improving the performance of the HONG network with boosting

This paper gives a brief description of a hierarchical architecture (HONG) that has been described elsewhere. The learning algorithm it uses is a mixed unsupervised/supervised method with most of the learning being unsupervised. The architecture generates multiple classifications for every data pattern presented, and combines them to obtain the final classification. The main purpose of this paper is to show how boosting can be used to improve the performance of the HONG classifier.

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