Unsupervised Learning

Craig Starbuck ()

A chapter in The Fundamentals of People Analytics, 2023, pp 261-282 from Springer

Abstract: Abstract This chapter covers dimension reduction techniques that have utility in exploring and confirming the factor structure of psychological instrumentation; techniques include exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and principal components analysis (PCA). K-means and hierarchical clustering methods are examined for surfacing patterns and insights in unsupervised settings in which there is no outcome variable.

Date: 2023
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:978-3-031-28674-2_14

Ordering information: This item can be ordered from
http://www.springer.com/9783031286742

DOI: 10.1007/978-3-031-28674-2_14

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 ().