tSNE {structToolbox} | R Documentation |
t-Distributed Stochastic Neighbor Embedding (tSNE) class. This object can be used to train/apply tSNE models to DatasetExperiment objects.
tSNE( dims = 2, perplexity = 30, max_iter = 100, theta = 0.5, check_duplicates = FALSE, init = NULL, eta = 200, ... )
dims |
integer; Output dimensionality (default: 2) |
perplexity |
numeric; Perplexity parameter (should not be bigger than 3 * perplexity < nrow(X) - 1, see details for interpretation) |
max_iter |
integer; Number of iterations (default: 1000) |
theta |
numeric; Speed/accuracy trade-off (increase for less accuracy), set to 0.0 for exact TSNE (default: 0.5) |
check_duplicates |
logical; Checks whether duplicates are present. It is best to make sure there are no duplicates present and set this option to FALSE, especially for large datasets (default: TRUE) |
init |
Initial locations of the objects. If NULL, random initialization will be used. If NULL then |
eta |
numeric; Learning rate (default: 200.0) |
... |
additional slots and values passed to struct_class |
This object is a wrapper for Rtsne::Rtsne.
struct object
M = tSNE()