关键词: M-ary, 支持向量机, 纠错编码, 多类分类, 最小码间距离, 输出校正码

Abstract: M-ary Support Vector Machine (M-ary SVM) for multi-category classification has the advantage of simple structure, but the disadvantage of weak generalization ability. This paper presented an enhanced M-ary SVM algorithm in combination with error correction coding theory. The main idea of the approach was to generate a group of best codes based on information codes derived from the original category flags information, then utilize such codes as the basis for training the classifier, while in the final feed-forward phase the output codes composed of each sub-classifier could be corrected by error detection and correction principle if there exists any identifying error. The experimental results confirm the effectiveness of the improved algorithm brought about by introducing as few sub-classifiers as possible.

Key words: M-ary, Support Vector Machine (SVM), error correction coding, multi-category classification, minimum code distance, output correction code