Feature selection for high-dimensional multi-category data using PLS-based local recursive feature elimination

作者：

Highlights：

• Present a feature selection framework based on local recursive feature elimination.

• Propose a new Partial Least Squares (PLS) based local recursive feature elimination algorithm.

• Obtain better performance while work effectively for high-dimensional multi-category data.

摘要

•Present a feature selection framework based on local recursive feature elimination.•Propose a new Partial Least Squares (PLS) based local recursive feature elimination algorithm.•Obtain better performance while work effectively for high-dimensional multi-category data.

论文关键词：High-dimensional multi-category problem,Partial least squares,Recursive feature elimination,Feature selection

论文评审过程：Available online 30 August 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.08.043