A new method for feature selection based on intelligent water drops

Abstract

One of the trending research areas of data mining and machine learning is feature selection. Feature selection is used as a technique for improving classification accuracy of a classifier as well as a more convenient way for visualization of data. In this paper, a new method for feature subset selection, based on intelligent water drops algorithm is proposed. Intelligent water drops algorithm is a metaheuristic algorithm which is inspired from movement of water drops in nature. In the proposed method, a new objective function which is suitable for intelligent water drops algorithm is introduced. The objective function is designed such that the selected feature vector would obtain a good classification accuracy as well as providing a good generalization degree. According to the experiments, the use of proposed approach leads to more accurate results as well as significant reduction in number of features.