A Task Decomposition Algorithm Based on the Distribution of Input Pattern Vectors for Classification Problems

Seiji Ishihara, Harukazu Igarashi

研究成果: Article

抄録

This paper proposes an algorithm for decomposing a multi-class classification problem into a set of two-class classification problems. The algorithm divides a set of input pattern vectors corresponding to each class into subsets according to the distribution of the selected input pattern vectors. The distribution is represented by Gaussian mixture models which are estimated by EM algorithm with MDL criterion. In this paper, the algorithm applied for constructing a modular neural network. Experimental results showed that the algorithm simplifies multi-class classification problems efficiently.

元の言語English
ページ(範囲)1043-1048
ページ数6
ジャーナルIEEJ Transactions on Electronics, Information and Systems
125
発行部数7
DOI
出版物ステータスPublished - 2005

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Decomposition
Neural networks

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

これを引用

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