Titlebook: Automating the Design of Data Mining Algorithms; An Evolutionary Comp Gisele L. Pappa,Alex Freitas Book 2010 Springer-Verlag Berlin Heidelb

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Introduction,rning data mining, the focus is on rule induction algorithms, which have the advantage of discovering knowledge expressed in the form of . classification rules that can be easily interpreted by the user, such as: . (.=.) and (.=.) . (.=.). Concerning evolutionary computation, the focus is on genetic

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Genetic Programming for Classification and Algorithm Design,ation task of data mining. In this first part, the chapter first explains important differences between classification models and classification algorithms - a crucial point to understand the contribution of this book, since the proposed genetic programming system produces a classification algorithm

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Automating the Design of Rule Induction Algorithms,ased genetic programming system for automatically evolving the design of rule induction algorithms. First, this chapter describes the grammar used by the system, which incorporates background knowledge about how human experts manually design a rule induction algorithm. Next, this chapter describes a

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