A task decomposition algorithm using mixtures of normal distributions for classification problems

Seiji Ishihara, Harukazu Igarashi

研究成果: Conference contribution

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 in each class into subsets according to the distribution of the selected input pattern vectors. The distribution is represented by a mixture of normal distributions, and the number of subsets is defined by using MDL criterion. The algorithm can be applied for constructing an effective modular neural network. We show also the experimental results of the construction and the advantages of the algorithm.

本文言語English
ホスト出版物のタイトルProceedings - Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006
DOI
出版ステータスPublished - 2006 12 1
イベント6th International Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006 - Auckland, New Zealand
継続期間: 2006 12 132006 12 15

出版物シリーズ

名前Proceedings - Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006

Conference

Conference6th International Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006
CountryNew Zealand
CityAuckland
Period06/12/1306/12/15

ASJC Scopus subject areas

  • Computer Science(all)

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