3. GAP: Constructing and selecting features with evolutionary computing

Abstract

The use of machine learning techniques to automatically analyze data for information is becoming increasingly widespread. In this chapter 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. 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. A Genetic Algorithm is used to determine which set of features is the most predictive. Using ten well-known data sets we show that our approach, in comparison to C4.5 alone, provides marked improvement in a number of cases.