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conference paper
Mixtures of Experts Estimate A Posteriori Probabilities
Moerland, Perry
1997
Artificial Neural Networks — ICANN'97
The mixtures of experts (ME) model offers a modular structure suitable for a divide-and-conquer approach to pattern recognition. It has a probabilistic interpretation in terms of a mixture model, which forms the basis for the error function associated with MEs. In this paper, it is shown that for classification problems the minimization of this ME error function leads to ME outputs estimating the a posteriori probabilities of class membership of the input vector.
Type
conference paper
Authors
Moerland, Perry
Editors
Gerstner, W.
•
Germond, A.
•
Hasler, M.
•
Nicoud, J. -D.
Publication date
1997
Publisher
Published in
Artificial Neural Networks — ICANN'97
Publisher place
Berlin
Series title/Series vol.
Lecture Notes in Computer Science; 1327
Start page
499
End page
504
Note
IDIAP-RR 97-07
EPFL units
Event name | Event place | Event date |
Lausanne, Switzerland | October 8–10, 1997 | |
Available on Infoscience
March 10, 2006
Use this identifier to reference this record