Analysis of separating surfaces formed by a random subspace classifier

Authors:
D. V. Zhora
Affiliations:
Institute of Program Systems, National Academy of Sciences of Ukraine, Kiev, Ukraine
Venue:
Cybernetics and Systems Analysis
Year:
2006

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Abstract

The discriminating capabilities of a random subspace classifier are considered. As a result of analysis of the probability density distribution of threshold values, an estimate is obtained for the minimum distinguishable distance. Real examples of separating surfaces for classical two-imensional problems are given. An algorithm is proposed for local averaging of a synapse matrix to improve the classifier performance in solving problems with overlapping probability distributions. The random subspace classifier is proved to be universal.