关键词: 特征选择, 搜索策略, 评价准则, 特征选择分类

Abstract: As a data preprocessing process, feature selection plays an important role in data mining, pattern recognition and machine learning. Through feature selection, the complexity of the problem can be reduced, and the prediction accuracy, robustness and interpretability of the learning algorithm can be improved. This paper introduces the framework of feature selection methods, and focuses on the two processes of generating feature subsets and evaluation criteria. The feature selection algorithms are classified according to different combinations of feature selection and learning algorithms, and the advantages and disadvantages of various methods are analyzed. The existing problems of existing feature selection algorithms are discussed, and some research difficulties and research directions are proposed.

Key words: feature selection, search strategy, evaluation criteria, feature selection classification