计算机科学 ›› 2017, Vol. 44 ›› Issue (3): 242-246.doi: 10.11896/j.issn.1002-137X.2017.03.050
李睿,王晓丹
LI Rui and WANG Xiao-dan
摘要： 基于相关向量机(Relevance Vector Machine,RVM)可以输出各类别成员概率的特点,对RVM二分类模型分别采用多元sigmoid方法和pairwise coupling方法,将其扩展为一对多分类器和一对一分类器,实现了多类分类及概率输出。基于人工高斯数据集和UCI数据集的实验仿真结果表明,所提方法不仅能够准确地求解样本后验概率,而且运行效率也比较高,同时能够保证较高的分类正确率。
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