Evolutionary rule generation classification and its application to multi-class data
作者： Susan E. Bedingfield , Kate A. Smith
关键词: Evolutionary music 、 Interactive evolutionary computation 、 Cultural algorithm 、 Artificial intelligence 、 Machine learning 、 Decision tree 、 Data mining 、 ID3 algorithm 、 Evolutionary programming 、 Incremental decision tree 、 Evolutionary algorithm 、 Mathematics
摘要: This paper considers an evolutionary algorithm based on information system for generating classification rules. Custom genetic operators and a multi-objective fitness function are designed this representation. The approach has previously been illustrated using binary class data set. In we explore the possibility of multi-class accuracy rules produced by compared to those obtained decision tree technique same data. advantages over more traditional structure discussed.
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