论文标题
连续半监督的非负基质分解
Continuous Semi-Supervised Nonnegative Matrix Factorization
论文作者
论文摘要
非负矩阵分解可用于以无监督的方式自动检测语料库中的主题。该技术等于非负矩阵作为两个较低等级的非负矩阵的乘积。在本文中，我们表明这种分解可以与连续响应变量上的回归结合使用。实际上，该方法的性能要比确定主题并恢复可解释性后进行的回归要好。
Nonnegative matrix factorization can be used to automatically detect topics within a corpus in an unsupervised fashion. The technique amounts to an approximation of a nonnegative matrix as the product of two nonnegative matrices of lower rank. In this paper, we show this factorization can be combined with regression on a continuous response variable. In practice, the method performs better than regression done after topics are identified and retrains interpretability.
