An optimization Algorithm of LVQ Neural Network Classification by GA
Liang Liu, Xiao Hong He, Hao Sun · Applied Mechanics and Materials · 2013
This paper describes a dimension reduction method of input vector to improve classification efficiency of LVQ neural network, where GA is used to decrease the redundancy of input data. And in order to solve the initial weight vector sensitivity, GA is also employed to optimize the initial vector. The experimental results on the UCI data sets demonstrate that the efficiency and accuracy of our LVQ network by GA is higher than general LVQ neural network classification algorithm.