Principal Components
Omar Hijab
Additional contact information
Omar Hijab: Temple University, Department of Mathematics
Chapter Chapter 3 in Math for Data Science, 2025, pp 121-186 from Springer
Abstract:
Abstract In this chapter, we look at the two fundamental methods of breaking or decomposing a matrix into elementary components, the eigenvalue decomposition and the singular value decomposition, then we apply this to principal component analysis.
Date: 2025
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-89707-8_3
Ordering information: This item can be ordered from
http://www.springer.com/9783031897078
DOI: 10.1007/978-3-031-89707-8_3
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().