A Binary I-Ching Divination Evolutionary Algorithm for Feature Selection

Abstract

Feature selection is used to extract the most essential features from the data without degrading the performance of an algorithm, especially a classification algorithm. Various evolutionary algorithms (EAs) combined with classification algorithms are commonly used for feature selection. This paper suggests an innovative feature selection algorithm based on I-Ching Divination Evolutionary Algorithm, called binary IDEA (BIDEA). The main idea is to use a series of hexagrams encoded as binary vectors, which is called the hexagram state to represent the solutions of selected features. After three flexible operations, intrication, turnover and mutual, the transformed hexagram state can be obtained as candidate solutions. Then the optimized hexagram state can be searched to form the new state in the next iteration by evaluating candidate solutions. Experiments checked out with standard datasets reveal that the proposed BIDEA performs better in terms of classification accuracy, precision, recall and feature reduction than the competing feature selection methods.