Content area

Abstract

Principal component analysis (PCA) simplifies the complexity in high-dimensional data while retaining trends and patterns. It does this by transforming the data into fewer dimensions, which act as summaries of features.

Details

Title
Points of Significance: Principal component analysis
Author
Lever, Jake; Krzywinski, Martin; Altman, Naomi
Pages
641-642
Publication year
2017
Publication date
Jul 2017
Publisher
Nature Publishing Group
ISSN
15487091
e-ISSN
15487105
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/nmeth.4346
ProQuest document ID
1917969320
Copyright
Copyright Nature Publishing Group Jul 2017