tSNE {structToolbox} | R Documentation |
t-Distributed Stochastic Neighbor Embedding.
tSNE( dims = 2, perplexity = 30, max_iter = 100, theta = 0.5, check_duplicates = FALSE, init = NULL, eta = 200, ... )
dims |
(numeric) The number of tSNE dimensions computed. The default is |
perplexity |
(numeric) Perplexity parameter. The default is |
max_iter |
(numeric) The maximum number of tSNE iterations. The default is |
theta |
(numeric) Speed/accuracy trade-off. A value of 0 gives an exact tSNE. The default is |
check_duplicates |
(logical) Check for duplicates. Allowed values are limited to the following:
The default is |
init |
(NULL, data.frame, DatasetExperiment) A set of coordinates for initialising the tSNE algorithm. NULL uses random initialisation. The default is |
eta |
(numeric) The learning rate parameter. The default is |
... |
Additional slots and values passed to |
This object makes use of functionality from the following packages:
Rtsne
A tSNE
object with the following output
slots:
Y | (DatasetExperiment) |
van der Maaten L, Hinton G (2008). “Visualizing High-Dimensional Data Using t-SNE.” Journal of Machine Learning Research, 9, 2579-2605.
van der Maaten L (2014). “Accelerating t-SNE using Tree-Based Algorithms.” Journal of Machine Learning Research, 15, 3221-3245.
Krijthe JH (2015). Rtsne: T-Distributed Stochastic Neighbor Embedding using Barnes-Hut Implementation. R package version 0.15, https://github.com/jkrijthe/Rtsne.
M = tSNE()