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中文摘要：
单实例多标签分类是指一个样本拥有多个标签的分类问题,对此提出了一种基于半模糊核聚类和模糊支持向量机的多标签分类算法。该算法采用一对一分解策略将多类多标签数据集分解为多个两类双标签数据子集,在每个子集上训练两类双标签模糊支持向量机。为提高分类器的性能引入了半模糊核聚类技术。实验结果表明,与现有的一些算法相比新算法具有其优越性。
英文摘要：
Single instance multi-label classification problem lies in that its sample may own multiple classes.Aiming at this subject a multi-label classification algorithm based on fuzzy support vector machine（FSVM） and semi-fuzzy kernel clustering is proposed.One versus one decomposition policy is used to decompose the multi-label problem into several binary class double label classification sub-problems.For each sub-problem,a sub-classifier using binary class double label FSVM model is built.To improve the classification performance,a kind of semi-fuzzy kernel clustering technology is employed.Experimental results show that the proposed method is superior to several existent multi-label classification algorithms.
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