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Abstract: The problem of determining the architecture of a multilayer perceptron together with the disadvantages of the standard backpropagation algorithm, directed the research towards algorithms that determine not only the weights but also the structure of the network necessary for learning the data. We propose a Constructive Algorithm with Multiple Operators using Statistical Test (MOST) for determining the architecture. The networks that are constructed by MOST can have multiple hidden layers with... (Update)
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BibTeX entry: (Update)
@misc{ aran-incremental,
author = "Oya Aran and Ethem Alpaydin",
title = "An Incremental Neural Network Construction Algorithm For Training Multilayer
Perceptron",
url = "citeseer.ist.psu.edu/article/aran03incremental.html" }
Citations (may not include all citations):372 The cascade-correlation learning architecture - Fahlman, Leibiere - 1990
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86 Pruning algorithms -- a survey (context) - Reed - 1993
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15 Toward generating neural network structures for function app.. (context) - Nabhan, Zomaya - 1994
3 The distribution of the range in samples from a normal popul.. (context) - Newman - 1939
2 Feedforward neural network construction using cross validati.. (context) - Setiono - 2001
2 Dynamic node creation in backpropogation networks (context) - Ash - 1989
2 Combined 5 x 2 cv f test for comparing supervised classifica.. (context) - Alpaydn - 1999
2 What's wrong with the cascadecorrelation learning: A project.. (context) - Hwang, You et al. - 1996
2 CARVE - a constructive algorithm for real valued examples (context) - Young, Downs - 1998
http://www.cs.toronto.edu/delve/
http://www.ics.uci.edu/mlearn/MLRepository.html
http://lib.stat.cmu.edu/
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