期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2014
卷号：14
期号：5
页码：78-81
出版社：International Journal of Computer Science and Network Security
摘要：Feature selection is the process of eliminating features from the data set that are irrelevant with respect to the task to be performed. Feature selection is important for many reasons such as simplification, performance, computational efficiency and feature interpretability. It can be applied to both supervised and unsupervised learning methodologies. Such techniques are able in improving the efficiency of various machine learning algorithms and that of training as well. Feature selection speed up the run time of learning, improves data quality and data understanding
