setup_tSNE: Setup tSNE parameters.
In egenn/rtemis: Machine Learning and Visualization

View source: R/10_S7_DecompositionParameters.R

setup_tSNE

R Documentation

Setup tSNE parameters.

Description

Setup tSNE parameters.

Usage

setup_tSNE(
  k = 2L,
  initial_dims = 50L,
  perplexity = 30,
  theta = 0.5,
  check_duplicates = TRUE,
  pca = TRUE,
  partial_pca = FALSE,
  max_iter = 1000L,
  verbose = getOption("verbose", FALSE),
  is_distance = FALSE,
  Y_init = NULL,
  pca_center = TRUE,
  pca_scale = FALSE,
  normalize = TRUE,
  stop_lying_iter = ifelse(is.null(Y_init), 250L, 0L),
  mom_switch_iter = ifelse(is.null(Y_init), 250L, 0L),
  momentum = 0.5,
  final_momentum = 0.8,
  eta = 200,
  exaggeration_factor = 12,
  num_threads = 1L
)

Arguments

`k`	Integer: Number of components.
`initial_dims`	Integer: Initial dimensions.
`perplexity`	Integer: Perplexity.
`theta`	Float: Theta.
`check_duplicates`	Logical: If TRUE, check for duplicates.
`pca`	Logical: If TRUE, perform PCA.
`partial_pca`	Logical: If TRUE, perform partial PCA.
`max_iter`	Integer: Maximum number of iterations.
`verbose`	Logical: If TRUE, print messages.
`is_distance`	Logical: If TRUE, `x` is a distance matrix.
`Y_init`	Matrix: Initial Y matrix.
`pca_center`	Logical: If TRUE, center PCA.
`pca_scale`	Logical: If TRUE, scale PCA.
`normalize`	Logical: If TRUE, normalize.
`stop_lying_iter`	Integer: Stop lying iterations.
`mom_switch_iter`	Integer: Momentum switch iterations.
`momentum`	Float: Momentum.
`final_momentum`	Float: Final momentum.
`eta`	Float: Eta.
`exaggeration_factor`	Float: Exaggeration factor.
`num_threads`	Integer: Number of threads.