A Large-Scale Data Classifying Approach Based on GP

Abstract

he method that the utility of genetic programming (GP) is used to create and use ensembles in data mining is demonstrated in the paper . Given its representational power in the model of complex non-linearities in the data, GP is seen to be effective at learning diverse patterns in the data. With different models capturing varied data relationships, GP models are ideally suited for combination in ensembles. Experimental results show that different GP models are dissimilar both in terms of the functional form as well as with respect to the variables defining the models.