An enhanced M-ary SVM algorithm for multi-category classification and its application
详细信息 查看全文
- 作者：Yi YanAuthor Vitae ; WeiKai ZhengAuthor Vitae ; Jian BaoAuthor Vitae ; Ran LiuAuthor Vitae
- 关键词：M-ary SVM ; Multi-category classification ; Error correcting code ; Minimum code distance
- 刊名：Neurocomputing
- 出版年：2016
- 出版时间：26 April 2016
- 年：2016
- 卷：187
- 期：Complete
- 页码：119-125
- 全文大小：1443 K
文摘
In this paper, an enhanced M-ary SVM algorithm in combination with error correction coding method is presented for multi-category classification. The main process of the approach is divided into three steps. It is firstly to generate a group of best codes based on information codes derived from the original category flags information. Secondly, it is to utilize such codes as the basis for training the classifier. The third step is the final feed-forward phase. The output codes composed of each sub-classifier are corrected by error detection and correction principle whenever any identifying error occurs. The improved algorithm not only maintains the highly simplified architecture of the standard M-ary algorithm, but also improves its generalization ability. The experimental results confirms the effectiveness of the improved algorithm brought about by introducing as few sub-classifiers. Finally, an application example for shuttle kiln control system is shown.