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判别最小平方有序回归*

DOI: 10.16451/j.cnki.issn1003-6059.201506008, PP. 535-541

Keywords: 有序回归,最小平方回归(LSR),累积标号,间隔扩大

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Abstract:

有序回归是特殊的机器学习范式,其目标是利用数据间内在的序标号以划分模式.尽管众多算法相继提出,但经典的最小平方回归(LSR)尚未应用于有序回归场景.为此,文中采用累积标号编码和间隔扩大策略,在LSR基础上提出判别最小平方有序回归(DLSOR).DLSOR在对回归函数无需施加约束的前提下,仅通过改造标号实现有序信息的嵌入和类间间隔的扩大,从而确保DLSOR在与LSR具有相当模型复杂度的同时,既保证较高的分类精度,又获得较低的平均绝对误差.实验验证DLSOR在提升有序回归性能上的优越性.

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