TSNE: t-distributed Stochastic Neighbor Embedding

In fdm2id: Data Mining and R Programming for Beginners

t-distributed Stochastic Neighbor Embedding

Description

Return the t-SNE dimensionality reduction.

Usage

TSNE(x, perplexity = 30, nstart = 10, seed = NULL, ...)

Arguments

x	A numeric dataset (data.frame or matrix).
perplexity	Specification of the perplexity.
nstart	How many random sets should be chosen? The embedding with the lowest final cost is kept.
seed	A specified seed for random number generation.
...	Other parameters.

Value

The Rtsne result. Rtsne requires distinct observations, so duplicated rows of x are removed before fitting; the returned Y (and costs) are then expanded back to nrow (x) rows, in the order of x, so that they can be used directly alongside the original dataset – duplicated observations simply share the same coordinates.

See Also

Rtsne

Examples

require (datasets)
data (iris)
TSNE (iris [, -5])

fdm2id documentation built on Aug. 28, 2026, 9:07 a.m.