Feature Selection using Differential Evolution with Binary Mutation Scheme

In this paper the use of an evolutionary computational algorithm such Differential Evolution have been studied for their use in feature selection problems. Feature selection is rapidly increasing in importance due to the exponential increase in the size of datasets. The dimensionality problem arising due to these large datasets can be dealt with by using feature selection, which provides a multitude of advantages when it comes to datasets. The advantages have been discussed in the paper. The use of Differential Evolution in this regard is a novel approach and provides us with comparable results with existing algorithms like GA. This paper also deals with the approach that involves changing the mutation scheme to allow for conversion to binary before selecting the features.