tsne.matrix: tsne.matrix implements t-Distributed Stochastic Neighbor...

Description Usage Arguments Examples

View source: R/tsner.R

Description

tsne.matrix implements t-Distributed Stochastic Neighbor Embedding (t-SNE) for matrix inputs

Usage

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## S3 method for class 'matrix'
tsne(
  X,
  dims = 2,
  initial_dims = -1,
  perplexity = 30,
  max_iter = 100,
  pca = FALSE,
  theta = 0.6,
  verbose = FALSE
)

Arguments

X

matrix; Data matrix

dims

integer; Output dimensionality (default: 2)

initial_dims

integer; the number of dimensions that should be retained in the initial PCA step (default: -1 (all))

perplexity

numeric; Perplexity parameter

max_iter

integer; Number of iterations (default: 1000)

pca

logical; Whether an initial PCA step should be performed (default: FALSE)

theta

numeric; Speed/accuracy trade-off (increase for less accuracy, default: 0.5)

verbose

logical; Whether progress updates should be printed (default: FALSE)

Examples

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## Not run: 
tsnedf <- tsne(X, dims, initial_dims, perplexity, max_iter, pca, theta, verbose)

## End(Not run)

lejon/tsner documentation built on May 19, 2021, 3:02 p.m.