Using a Neural Network and Genetic Algorithm to Extract Decision Rules
نویسندگان
چکیده
Rule extraction from neural networks often focusses on exact equivalence and is often tested on relatively small canonical examples. We apply genetic algorithms to the extract approximate rules from neural networks. The method is robust and works with large networks. We compare the results with rules obtained using state of the art decision tree methods and achieve superior performance to straight forward application of the WEKA implementation of the C5 algorithm, J48.PART.
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تاریخ انتشار 2003