论文标题

使用精确标签嵌入的基于角度的分层分类

Angle-based hierarchical classification using exact label embedding

论文作者

Fan, Yiwei, Lu, Xiaoling, Liu, Yufeng, Zhao, Junlong

论文摘要

层次分类问题通常在实践中出现。但是,大多数现有方法并未完全利用类标签之间的分层信息。在本文中,提出了一种新型的标签嵌入方法,该方法可以准确地保持标签的层次结构,并显着降低了假设空间的复杂性。基于新提出的标签嵌入方法,开发了一种新的基于角度的分类器用于分层分类。此外,为了处理大量数据,设计了一种新的(加权)线性损耗,该损耗具有封闭形式的解决方案,并且在计算上是有效的。建立了新方法的理论特性,并与其他方法进行了深入的数值比较。文档分类中的模拟和应用都证明了该方法的优势。

Hierarchical classification problems are commonly seen in practice. However, most existing methods do not fully utilize the hierarchical information among class labels. In this paper, a novel label embedding approach is proposed, which keeps the hierarchy of labels exactly, and reduces the complexity of the hypothesis space significantly. Based on the newly proposed label embedding approach, a new angle-based classifier is developed for hierarchical classification. Moreover, to handle massive data, a new (weighted) linear loss is designed, which has a closed form solution and is computationally efficient. Theoretical properties of the new method are established and intensive numerical comparisons with other methods are conducted. Both simulations and applications in document categorization demonstrate the advantages of the proposed method.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源