TY - JOUR
T1 - A Task Decomposition Algorithm Based on the Distribution of Input Pattern Vectors for Classification Problems
AU - Ishihara, Seiji
AU - Igarashi, Harukazu
PY - 2005
Y1 - 2005
N2 - 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.
AB - 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.
KW - EM algorithm
KW - classification problem
KW - minimum description length criterion
KW - modular neural network
UR - http://www.scopus.com/inward/record.url?scp=85024721631&partnerID=8YFLogxK
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U2 - 10.1541/ieejeiss.125.1043
DO - 10.1541/ieejeiss.125.1043
M3 - Article
AN - SCOPUS:85024721631
SN - 0385-4221
VL - 125
SP - 1043
EP - 1048
JO - IEEJ Transactions on Electronics, Information and Systems
JF - IEEJ Transactions on Electronics, Information and Systems
IS - 7
ER -