关键词: 多标签分类, ML-kNN算法, 聚类, 大数据集

Abstract: Multi-label k Nearest Neighbor（ML-kNN） algorithm is a lazy learning approach and has successfully been developed in real application. With the increasing amount of information, it is necessary for the ML-kNN algorithm to be applied to large data sets. This paper firstly conducts clustering algorithm to separate the dataset into several parts, and then, each of which conducts ML-kNN classification. And a series of experiments are carried out on four different datasets. The experimental results show that ML-kNN algorithm proposed works well in terms of accuracy and efficient.

Key words: multi-label classification, Multi-Label k Nearest Neighbor（ML-kNN）, cluster, big data set