关键词: 球结构支持向量机, 欧氏距离, 多标签分类, 多类分类, 主动学习方法

Abstract: In order to implement the multi-label classification of data and reduce the overload of multi-label training samples, an algorithm combined with sphere structured Support Vector Machine （SVM） and active learning method was proposed. The labels of the samples in overlapping regions were determined according to distance difference value. The classification features of multi-label were analyzed. Then classifier was updated by closed neighbor method. The experimental results show that the method can achieve more efficient results using less training samples.

Key words: sphere structured support vector machine, Euclidean distance, multi-label classification, multi-class classification, active learning method