Genetic programming for attribute construction in data mining

Authors:
Fernando E. B. Otero;Monique M. S. Silva;Alex A. Freitas;Julio C. Nievola
Affiliations:
Pontificia Universidade Catolica do Parana, Curitiba, PR, Brazil;Computing Laboratory, University of Kent, Canterbury, Kent, UK;Pontificia Universidade Catolica do Parana, Curitiba, PR, Brazil;Pontificia Universidade Catolica do Parana, Curitiba, PR, Brazil
Venue:
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Year:
2003

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Abstract

For a given data set, its set of attributes defines its data space representation. The quality of a data space representation is one of the most important factors influencing the performance of a data mining algorithm. The attributes defining the data space can be inadequate, making it difficult to discover high-quality knowledge. In order to solve this problem, this paper proposes a Genetic Programming algorithm developed for attribute construction. This algorithm constructs new attributes out of the original attributes of the data set, performing an important preprocessing step for the subsequent application of a data mining algorithm.