基于标记相关性的多标记三支分类算法

A multi-label three-way classification algorithm based on label correlation

提出了一种基于标记相关性的多标记三支分类算法TML_LC,该算法利用三支决策模型将多标记样本空间划分为接受域、拒绝域和边界域,然后利用概率图模型构建标记之间的相关性,并应用于边界域的延迟决策,从而降低分类模型的时间复杂度,并提高分类模型的精度。

This paper uses the probability map model to the tag relationship is encoded, and three-way three decision models are used to solve the uncertainty of the data samples. A multi-label classification algorithm based on three-way decision-correlation correlation is proposed. The algorithm will solve the two-way decision problem in multi-label classification(TML_LC). The SVM mapping is divided into accepted domain, rejected domain and uncertain domain. The probability map model is used to consider the correlation between labels to transform the uncertainty of the uncertain domain, so as to improve the accuracy of the classification model.