2019
Unsupervised Feature Ranking and Selection Based on Autoencoders
ICASSP 2019accepted
Feature selection is one of the most important and widely-used dimension reduction techniques due to its efficiency and intractability of the results. In this paper, we propose a simple but efficient unsupervised feature ranking and selection method by exploiting the geometry of the original feature…