Multidimensional scaling: Difference between revisions

Revision as of 23:10, 16 October 2023

Revision as of 11:37, 23 October 2023

Line 120:

==Implementations==

*# [[ELKI]] includes two MDS implementations.

*# [[MATLAB]] includes two MDS implementations (for classical (''cmdscale'') and non-classical (''mdscale'') MDS respectively).

*# The [[R (programming language)|R programming language]] offers several MDS implementations, e.g. base ''cmdscale'' function, packages [https://CRAN.R-project.org/package=smacof smacof]<ref>{{Cite journal|last=Leeuw|first=Jan de|last2=Mair|first2=Patrick|date=2009|title=Multidimensional Scaling Using Majorization: SMACOF in R|url=http://www.jstatsoft.org/v31/i03/|journal=Journal of Statistical Software|language=en|volume=31|issue=3|doi=10.18637/jss.v031.i03|issn=1548-7660|doi-access=free}}</ref> (mMDS and nMDS), and [https://CRAN.R-project.org/package=vegan vegan] (weighted MDS).

*# [[scikit-learn]] contains function [http://scikit-learn.org/stable/modules/generated/sklearn.manifold.MDS.html sklearn.manifold.MDS].

== See also ==

{{Commons category|Multidimensional scaling}}

*# [[Data clustering]]

*# [[Factor analysis]]

*# [[Discriminant analysis]]

*# [[Dimensionality reduction]]

*# [[Distance geometry]]

*# [[Cayley–Menger determinant]]

*# [[Sammon mapping]]

*# [[Iconography of correlations]]

== References ==