d_TSNE: t-distributed Stochastic Neighbor Embedding

View source: R/d_TSNE.R

d_TSNER Documentation

t-distributed Stochastic Neighbor Embedding

Description

Perform t-SNE decomposition using Rtsne::Rtsne

Usage

d_TSNE(
  x,
  k = 3,
  initial.dims = 50,
  perplexity = 15,
  theta = 0,
  check.duplicates = TRUE,
  pca = TRUE,
  max.iter = 1000,
  scale = FALSE,
  center = FALSE,
  is.distance = FALSE,
  verbose = TRUE,
  outdir = "./",
  ...
)

Arguments

x

Input matrix

k

Integer. Number of t-SNE components required

initial.dims

Integer: Number of dimensions to retain in initial PCA. Default = 50

perplexity

Numeric: Perplexity parameter

theta

Float: 0.0: exact TSNE. Increase for higher speed, lower accuracy. Default = 0

check.duplicates

Logical: If TRUE, Checks whether duplicates are present. Best to set test manually

pca

Logical: If TRUE, perform initial PCA step. Default = TRUE

max.iter

Integer: Maximum number of iterations. Default = 1000

scale

Logical: If TRUE, scale before running t-SNE using base::scale. Default = FALSE

center

Logical: If TRUE, and scale = TRUE, also center. Default = FALSE

is.distance

Logical: If TRUE, x should be a distance matrix. Default = FALSE

verbose

Logical: If TRUE, print messages to output

outdir

Path to output directory

...

Options for Rtsne::Rtsne

Value

rtDecom object

Author(s)

E.D. Gennatas

See Also

Other Decomposition: d_H2OAE(), d_H2OGLRM(), d_ICA(), d_Isomap(), d_KPCA(), d_LLE(), d_MDS(), d_NMF(), d_PCA(), d_SPCA(), d_SVD(), d_UMAP()


egenn/rtemis documentation built on Oct. 28, 2024, 6:30 a.m.