Genetic Programming for Attribute Construction in Data Mining
Lecture notes in computer sciencePublished 1 January 2003
Fernando E. B. Otero, Monique M. S. Silva, Alex A. Freitas, Júlio César Nievola
Citations107
SJR quartileQ2
SJR score0.35
SNIP0.55
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TL;DR
This paper proposes a Genetic Programming algorithm developed for attribute construction, which 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.
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.
Keywords
Computer Science
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