Relief特征选择算法最初由Kira和Rendell于1992年提出的一种著名的多变量过滤式特征选择算法，它也是一种基于样本学习的特征权重计算算法-Relief is a kind of feature weighting algorithm, which gives different weights according to the relevance of features and categories