Using the group genetic algorithm for attribute clustering
Tzung‐Pei Hong, Feng-Shih Lin, Chun-Hao Chen · 2012
In the past, the concept of performing the task of feature selection by attribute clustering was proposed. Hong et al. thus proposed several genetic algorithms for finding appropriate attribute clusters. In this paper, we attempt to improve the performance of the GA-based attribute-clustering process based on the grouping genetic algorithm (GGA). In our approach, the general GGA representation and operators are used to reduce the redundancy of chromosome representation for attribute clustering. At last, experiments are made to compare the efficiency of the proposed approaches and the previous ones.