Title: A Bayesian classifier lay using the adaptive construct algorithm of the CIF networks
Authors: Jiang, MH ×
Liu, DF
Deng, BX
Gielen, Georges #
Issue Date: 2004
Publisher: Springer
Series Title: Lecture Notes in Computer Science vol:3173 pages:876-881
Abstract: In paper we propose a Bayesian classifier for multiclass problem by using the merging RBF networks. The estimation of probability density function (PDF) with a Gaussian mixture model is used to update the expectation maximization algorithm. The centers and variances of RBF networks are gradually updated to merge the basis unites by the supervised gradient descent of the error energy function. The algorithms are used to construct the RBF networks and to reduce the number of basis units. The experimental results show the validity of our method which gives a smaller number of basis units and obviously outperforms the conventional RBF learning technique.
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - MICAS, Microelectronics and Sensors
× corresponding author
# (joint) last author

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