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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1619-7127 an just optimize its parameters..Includes supplementary mateData mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable

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Sofia D’souza,Prema K. V.,Seetharaman Balajill other components of the system related to the genetic programming algorithm itself - i.e., individual representation, population initialization, individual evaluation (based on a single-objective or multiobjective fitness function) and finally crossover and mutation operations.

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Diverse Education Within the Arts automation in data mining, since rule induction algorithms are normally manually designed by human experts. Thirdly, this chapter presents an overview of the proposed genetic programming system for automating the design of rule induction algorithms.

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Richard Yanagihara,Se Hun Gu,Jin-Won Songusing on a specific kind of genetic programming method called grammar-based genetic programming. As the name implies, this is a type of genetic programming method where the search for good programs is guided by a grammar, which incorporates background knowledge about the problem being solved.

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https://doi.org/10.1007/978-3-658-41852-6atasets with similar properties), investigating other types of search methods for automated algorithm design, automatically designing other types of classification algorithms (different from rule induction ones) or even other types of data mining algorithms, like clustering algorithms.

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Introduction, automation in data mining, since rule induction algorithms are normally manually designed by human experts. Thirdly, this chapter presents an overview of the proposed genetic programming system for automating the design of rule induction algorithms.

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Evolutionary Algorithms,using on a specific kind of genetic programming method called grammar-based genetic programming. As the name implies, this is a type of genetic programming method where the search for good programs is guided by a grammar, which incorporates background knowledge about the problem being solved.

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Automating the Design of Rule Induction Algorithms,ll other components of the system related to the genetic programming algorithm itself - i.e., individual representation, population initialization, individual evaluation (based on a single-objective or multiobjective fitness function) and finally crossover and mutation operations.