Optimizing classification techniques using Genetic Programming approach

Genetic programming (GP) is a branch of genetic algorithms (GA) that searches for the best operation or computer program in search space of operations. At the same time classification is a data mining technique used to build model of data classes which can be used to predict future trends. In this paper GP has been employed for the implementation of the classification technique. GP properties can facilitate generating new and optimized classification rules that are not discovered by the existing traditional classification techniques. In addition we will show that GA approach is superior to traditional methods in regard to performance both on time and space requirements for processing.