一种基于Dempster-Shafer理论的分类器组合算法

An algorithm to combine classifiers based on Dempster-Shafer theory

提出了基于Dempster -Shafer理论进行多个神经网络分类器组合的一种可行算法 ,该算法考虑了每个分类器对不同类的识别能力不同这一经验知识 .在UCI数据库的分类和一个多传感器融合工件识别系统中的应用结果 。

A practical algorithm to combine the neural networks classifiers based on Dempster-Shafer theory is proposed. The influence of the fact that every classifier has different classification ability for different class is considered. Several databases of UCI repository and a multiple sensor fusion system for workpiece identification are tested, showing the validity of the algorithm.