Description: hallenge to the use of supervised neural networks in data mining applications
is to get explicit knowledge from these models. For this purpose, a clustering genetic algorithm
for rule extraction from artiÞ cial neural networks is developed. The methodology is based on the
clustering of the hidden unit activation values. A simple encoding scheme that yields to constant-
length chromosomes is used, thus allowing the application of the standard genetic operators. Besides,
a consistent algorithm to avoid some of the drawbacks of this kind of representation is also developed.
The individual Þ tness is determined b
To Search:
- [DIANA] - Data mining, DIANA algorithm, the data s
- [SA_GA] - Genetic simulated annealing algorithm ba
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