A prototype selection algorithm based on voting mechanism
一种基于投票机制的代表点选择算法

Prototype selection is an important step in data mining and pattern recognition; it is an efficient way to improve the classification accuracy and runing efficiency. This paper proposed a new prototype selection algorithm based on voting mechanism, which could see that most of the selected prototypes are distributed among the classification border and are not outliers. And it is in favor of improving the classification accuracy and efficiency of the nearest neighbor classifier. Experiments on the proposed algorithm and some other famous prototype selection algorithms show the prototype selection algorithm based on voting mechanism has some advantages in improving both the classification accuracy and the data reduction rate.