Discriminative Semi-Supervised Feature Selection via Rescaled Least Squares Regression-Supplement

2018-02-08

Proceedings of the AAAI Conference on Artificial Intelligence, 32

Volume

Thirty-Second AAAI Conference on Artificial Intelligence 2018

Student Abstract Track

In this paper, we propose a Discriminative Semi-Supervised Feature Selection (DSSFS) method. In this method, a ε-dragging technique is introduced to the Rescaled Linear Square Regression in order to enlarge the distances between different classes. An iterative method is proposed to simultaneously learn the regression coefficients, ε-draggings matrix and predicting the unknown class labels. Experimental results show the superiority of DSSFS.

10.1609/aaai.v32i1.12177