Finding feature transformation functions using genetic algorithm

Authors:
Eun Yeong Ahn;Tracy Mullen;John Yen
Affiliations:
The Pennsylvania State University, University Park, PA, USA;The Pennsylvania State University, University Park, PA, USA;The Pennsylvania State University, University Park, PA, USA
Venue:
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Year:
2010

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Abstract

Identifying a good set of features is critical to the performance of learning algorithms such as classifiers. Previous methods have focused on either selecting a subset of features or transforming features using principle components analysis. In this paper, we propose a genetic algorithm approach that searches for a good feature transformation function over a subset of features using a novel representation scheme with novel reproduction operators. Preliminary experimental results using the UCI data set show promising results.