论文标题
移动窗口回归：一种新颖的序数回归方法
Moving Window Regression: A Novel Approach to Ordinal Regression
论文作者
论文摘要
本文提出了一种新型的序数回归算法，称为移动窗口回归（MWR）。首先，我们提出了相对等级的概念（$ρ$ -Lank），这是一种新的订单表示方案和参考实例。其次，我们开发了全球和本地相对回归器（$ρ$ -Regressors），以分别预测整个和特定等级范围内的$ρ$ ranks。第三，我们通过选择两个参考实例来形成搜索窗口，然后估算窗口中的$ρ$ lank，从而完善初始排名估计。广泛的实验结果表明，所提出的算法在各种基准数据集上实现了面部年龄估计和历史颜色图像分类的最新性能。这些代码可在https://github.com/nhshin-mcl/mwr上找到。
A novel ordinal regression algorithm, called moving window regression (MWR), is proposed in this paper. First, we propose the notion of relative rank ($ρ$-rank), which is a new order representation scheme for input and reference instances. Second, we develop global and local relative regressors ($ρ$-regressors) to predict $ρ$-ranks within entire and specific rank ranges, respectively. Third, we refine an initial rank estimate iteratively by selecting two reference instances to form a search window and then estimating the $ρ$-rank within the window. Extensive experiments results show that the proposed algorithm achieves the state-of-the-art performances on various benchmark datasets for facial age estimation and historical color image classification. The codes are available at https://github.com/nhshin-mcl/MWR.
