关键词: 最近邻, 快速分类, 多标签数据, 快速多标签数据分类算法（FKMC）

Abstract: For overcoming the limitation of ML-KNN on the aspect of categorization efficiency，a fast KNN-based multi-label categorization algorithm named FKMC is proposed，where the local information of the k-nearest neighbors of those unclassified data instances is used to do ranking categorization on these instances.To an unclassified instance，its k-nearest neighbors are selected from the classified instances set in the first step，and then ranking categorization on it is done in light of the number of labels assigned to each nearest neighbor and the number of the nearest neighbors owning each label.Simulation results show that the method of selecting the nearest neighbors affects the performance of a classifier obviously.The categorization effect of FKMC is similar with that of ML-KNN in most cases，and sometimes the former is even better.While on the aspect of categorization efficiency，FKMC outperforms ML-KNN remarkably.

Key words: nearest neighbors, fast classifying, multi-label data, Fast K-nearest neighbors based Multi-label Categorization（FKMC）