Appropriate initial component densities of mixture modeling for pattern recognition
説明
Some initial component densities are compared in a mixture model for pattern recognition. The EM algorithm is widely adopted in construction of a mixture density for approximating a class-conditional density. However, the algorithm is very sensitive to the number of component densities and the initial component densities themselves. The initial component densities are obtained by a clustering method. We report the results of comparison between clustering methods yielding non-overlapping clusters and methods yielding overlapping clusters.
収録刊行物
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- 1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)
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1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111) 2 216-220, 2002-11-27
IEEE
