Feature construction and selection using genetic programming and a genetic algorithm

Authors:
Matthew G. Smith;Larry Bull
Affiliations:
Faculty of Computing, Engineering & Mathematical Sciences, University of the West of England, Bristol, UK;Faculty of Computing, Engineering & Mathematical Sciences, University of the West of England, Bristol, UK
Venue:
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Year:
2003

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Abstract

The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is classified using the C4.5 decision tree learning algorithm. The Genetic Programming is used to construct new features from those available in the data, a potentially significant process for data mining since it gives consideration to hidden relationships between features. The Genetic Algorithm is used to determine which such features are the most predictive. Using ten well-known datasets we show that our approach, in comparison to C4.5 alone, provides marked improvement in a number of cases.