Digital Image Computing: Techniques and Applications (DICTA'05)
A Task Decomposition Algorithm Using Radial Basis Functions for Classification Problems
Cairns, Australia
December 06-December 08
ISBN: 0-7695-2467-2
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 RBF network, whose parameters are estimated according to the evaluation based on 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 effectively.
Citation:
Seiji Ishihara, Harukazu Igarashi, "A Task Decomposition Algorithm Using Radial Basis Functions for Classification Problems," dicta, pp.2, Digital Image Computing: Techniques and Applications (DICTA'05), 2005