tSNE implementation — rs_tsne • manifoldsR

Leverages the tSNE implementation in manifolds-rs - a very fast Rust-based implementation. You have two optimiser options: "bh" which tends to be faster on smaller datasets and "fft" for large data sets.

Usage

rs_tsne(
  embd,
  n_dim,
  perplexity,
  approx_type,
  tsne_params,
  seed,
  use_high_precision,
  verbose
)

Arguments

embd: Numerical matrix. The data to use to generate the embeddings. Should be of dimensions samples x features.
n_dim: Integer. Number of tSNE dimensions to return. Needs to be two, others are not supported.
perplexity: Numeric. The tSNE perplexity parameter.
approx_type: String. One of c("fft", "bh"). Which of the two approximations to use.
tsne_params: Named list. List that contains all of the key parameters for the tSNE generation.
seed: Integer. Seed for reproducibility.
use_high_precision: Optional logical. Controls fp32 vs fp64 for. If NULL will use sensible default thresholding.
verbose: Integer. If 0L -> silent or 1L for normal verbosity; 2L for detailed verbosity.

Value

The tSNE embeddings.