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Abstract: A new algorithm for neural network pruning is presented. Using this algorithm, networks with small number of connections and high accuracy rates for breast cancer diagnosis are obtained. We will then describe how rules can be extracted from a pruned network by considering only a finite number of hidden unit activation values. The accuracy of the extracted rules is as high as the accuracy of the pruned network. For the breast cancer diagnosis problem, the concise rules extracted from the network ... (Update)
Context of citations to this paper: More
.... in mind as a prior objective, a number of researchers have applied the method of extracting Boolean rules from neural networks [27,28,30]. Their results are encouraging, exhibiting both good performance and a reduced number of rules and relevant input variables....
.... having interpretability of the diagnostic as a prior objective, have applied the method of extracting Boolean rules from neural networks [40], 42] 43] Our own work on the evolution of fuzzy rules for the WBCD problem has shown that it is possible to obtain diagnostic systems...
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An Evolutionary Artificial Neural Networks Approach for Breast.. - Abbass (2002) (Correct)
Coevolutionary Fuzzy Modeling - Peņa-Reyes (2002) (Correct)
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0.5: A Penalty-Function Approach for Pruning Feedforward Neural Networks - Setiono (1994) (Correct)
0.4: FERNN: An Algorithm for Fast Extraction of Rules from Neural.. - Setiono, Leow (2000) (Correct)
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BibTeX entry: (Update)
R. Setiono. Extracting rules from pruned neural networks for breast cancer diagnosis. Artificial Intelligence in Medicine, pages 37--51, February 1996. http://citeseer.ist.psu.edu/setiono96extracting.html More
@article{ setiono96extracting,
author = "Rudy Setiono",
title = "Extracting rules from pruned networks for breast cancer diagnosis",
journal = "Artificial Intelligence in Medicine",
volume = "8",
number = "1",
pages = "37-51",
year = "1996",
url = "citeseer.ist.psu.edu/setiono96extracting.html" }
Citations (may not include all citations):667 UCI repository of machine learning databases (context) - Murphy, Aha - 1992
550 Parallel Distributed Processing (context) - Rumelhart, McClelland - 1986 ACM
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46 Pattern recognition via linear programming: theory and appli.. - Mangasarian, Setiono et al. - 1990
42 Learning algorithms for connectionist networks: applied grad.. (context) - Watrous - 1987
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16 Improving the convergence of the backpropagation algorithm (context) - van Ooyen, Nienhuis - 1992
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2 A desktop neural network for dermatology diagnosis (context) - Yoon, Brobst et al. - 1989
2 A node pruning algorithm for backpropagation network (context) - Chung, Lee - 1992
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The graph only includes citing articles where the year of publication is known.
Documents on the same site (http://www.comp.nus.edu.sg/~rudys/publications.html): More
Generating Concise and Accurate Classification Rules for Breast.. - Setioni (Correct)
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