摘要
在大数据分析和处理中有许多常用的降维方法,在线性降维中典型的方法有SVD分解和CUR分解,但是对这两种方法的使用条件和实际效果研究甚少。基于此,通过对SVD与CUR分解原理和实验结果的探讨,分析了这两种降维方法的使用条件和实际效果。
There are many common dimensionality reduction methods in big data analysis and processing,the typical linear dimension reduction methods include SVD decomposition and CUR decomposition,but few people explore the effect and conditions in using the two methods in the past,and a certain method may be taken under an inappropriate condition.This paper analyzes the SVD decomposition and CUR decomposition from both theory and experiment aspects,and discovery the effect and conditions in using the two methods.
出处
《中原工学院学报》
CAS
2014年第6期80-84,共5页
Journal of Zhongyuan University of Technology
关键词
SVD分解
TSVD
CUR分解
降维
SVD decomposition
TSVD
CUR decomposition
dimensionality reduction
