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