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README.md
In lmds: Landmark Multi-Dimensional Scaling
lmds
lmds: Landmark Multi-Dimensional Scaling
A fast dimensionality reduction method scaleable to large numbers of
samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension of
classical Torgerson MDS, but rather than calculating a complete distance
matrix between all pairs of samples, only the distances between a set of
landmarks and the samples are calculated.
library(lmds)
x <- as.matrix(iris[,1:4])
dimred <- lmds(x, ndim = 2)
qplot(dimred[,1], dimred[,2]) + labs(title = "lmds()") + theme_classic()
dimred <- cmdscale(dist(x))
qplot(dimred[,1], dimred[,2]) + labs(title = "cmdscale()") + theme_classic()
Execution time
The execution time of lmds() scales linearly with respect to the
dataset size. 
Latest changes
Check out news(package = "lmds") or NEWS.md for a full list
of
changes.
Recent changes in lmds 0.1.0
Initial release of lmds.
- A fast dimensionality reduction method scaleable to large numbers of
samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension
of classical Torgerson MDS, but rather than calculating a complete
distance matrix between all pairs of samples, only the distances
between a set of landmarks and the samples are calculated.
Try the lmds package in your browser
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lmds documentation built on Sept. 27, 2019, 5:03 p.m.
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lmds
lmds: Landmark Multi-Dimensional Scaling
A fast dimensionality reduction method scaleable to large numbers of samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension of classical Torgerson MDS, but rather than calculating a complete distance matrix between all pairs of samples, only the distances between a set of landmarks and the samples are calculated.
library(lmds)
x <- as.matrix(iris[,1:4])
dimred <- lmds(x, ndim = 2)
qplot(dimred[,1], dimred[,2]) + labs(title = "lmds()") + theme_classic()
dimred <- cmdscale(dist(x))
qplot(dimred[,1], dimred[,2]) + labs(title = "cmdscale()") + theme_classic()
Execution time
The execution time of lmds() scales linearly with respect to the
dataset size.
Latest changes
Check out news(package = "lmds") or NEWS.md for a full list
of
changes.
Recent changes in lmds 0.1.0
Initial release of lmds.
- A fast dimensionality reduction method scaleable to large numbers of samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension of classical Torgerson MDS, but rather than calculating a complete distance matrix between all pairs of samples, only the distances between a set of landmarks and the samples are calculated.
Try the lmds package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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