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.

Value

tSNEParameters object.

Details

Get more information on the parameters by running ?Rtsne::Rtsne.

Author

EDG