Modified KNN algorithm for multi-label learning
用于多标记学习的K近邻改进算法*

ML-KNN is an approach that employs KNN to solve multi-label problems,but it suffers from the problems of high time complexity and low classification accuracy.This paper proposed a modified algorithm WML-KNN to solve these problems.It combined data sampling and weighting into one approach,and resulted in the time complexity reduction and the classification accuracy improvement of the minority class data.Experimental results show that WML-KNN works better than other commonly used multi-label algorithms.