计算机科学 ›› 2021, Vol. 48 ›› Issue (11A): 102-105.doi: 10.11896/jsjkx.210300065
辛现伟1, 史春雷1, 韩雨琦1, 薛占熬2, 宋继华1
XIN Xian-wei1, SHI Chun-lei1, HAN Yu-qi1, XUE Zhan-ao2, SONG Ji-hua1
摘要: 三支决策(Three-Way Decision,3WD)作为一种新的粒计算方法,在处理不确定和不精确问题上具有独特的优势。针对标签传播算法(Label Propagation Algorithm,LPA)在节点更新过程中存在的较高随机不确定性和冗余性问题,提出了基于三支决策的增量标签传播算法(3WD_ILPA)。首先,给出了邻接模糊信息测度的概念和计算方法,并用于生成任意两节点间的概率转移矩阵。然后,将三支决策融入节点的动态更新过程,并把迭代更新后准确率最高的节点逐步增量添加到下一循环过程,直至收敛。此外,给出了3WD_ILPA算法的详细流程。最后,在ABIDE数据集上进行孤独症(Autistic Spectrum Disorder,ASD)识别实验,与传统机器学习、深度学习和迁移学习等方法的对比结果表明,所提方法具有更高的准确率。
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