tsne {maotai} | R Documentation |
t-SNE Embedding
Description
This function is a simple wrapper of Rtsne
function for
t-Stochastic Neighbor Embedding for finding low-dimensional structure of
the data embedded in the high-dimensional space.
Usage
tsne(data, ndim = 2, ...)
Arguments
data |
an |
ndim |
an integer-valued target dimension. |
... |
extra parameters to be used in |
Value
a named list containing
- embed
an
(n\times ndim)
matrix whose rows are embedded observations.- stress
discrepancy between embedded and origianl data as a measure of error.
Examples
## use simple example of iris dataset
data(iris)
mydat = as.matrix(iris[,1:4])
mylab = as.factor(iris[,5])
## run t-SNE and MDS for comparison
iris.cmds = cmds(mydat, ndim=2)
iris.tsne = tsne(mydat, ndim=2)
## extract coordinates and class information
cx = iris.cmds$embed # embedded coordinates of CMDS
tx = iris.tsne$embed # t-SNE
## visualize
# main title
mc = paste("CMDS with STRESS=",round(iris.cmds$stress,4),sep="")
mt = paste("tSNE with STRESS=",round(iris.tsne$stress,4),sep="")
# draw a figure
opar <- par(no.readonly=TRUE)
par(mfrow=c(1,2))
plot(cx, col=mylab, pch=19, main=mc)
plot(tx, col=mylab, pch=19, main=mt)
par(opar)
[Package maotai version 0.2.5 Index]