计算机科学
特征选择
聚类分析
特征提取
数据挖掘
模式识别(心理学)
选择(遗传算法)
人工智能
过程(计算)
原始数据
特征(语言学)
实施
语言学
操作系统
哲学
程序设计语言
作者
Ghojogh, Benyamin,Samad, Maria N.,Mashhadi, Sayema Asif,Kapoor, Tania,Ali, Wahab,Karray, Fakhri,Crowley, Mark
标识
DOI:10.48550/arxiv.1905.02845
摘要
Pattern analysis often requires a pre-processing stage for extracting or selecting features in order to help the classification, prediction, or clustering stage discriminate or represent the data in a better way. The reason for this requirement is that the raw data are complex and difficult to process without extracting or selecting appropriate features beforehand. This paper reviews theory and motivation of different common methods of feature selection and extraction and introduces some of their applications. Some numerical implementations are also shown for these methods. Finally, the methods in feature selection and extraction are compared.
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