Study on classification model based on relevance vector machine with genetic algorithm

Abstract

A novel classification method based on relevance vector machine with genetic algorithm is presented in the paper. In the model, genetic algorithm is applied to gain the suitable training parameters of relevance vector machine. State classification of roll bearing is applied to testify the classification ability of the proposed method, and state classification data of roll bearing are given. The experimental results show that relevance vector machine with genetic algorithm has higher classification accuracy than back-propagation neural network and support vector machine.