hbeta

beta

<p><code>hbeta</code> returns the perplexity and probability values for a row
   of data <code>D</code>.</p>

An implementation of multiple maps t-distributed stochastic
neighbor embedding (t-SNE). Multiple maps t-SNE is a method for
projecting high-dimensional data into several low-dimensional maps such that
non-metric space properties are better preserved than they would be by a single
map. Multiple maps t-SNE with only one map is equivalent to standard t-SNE.
When projecting onto more than one map, multiple maps t-SNE estimates a set
of latent weights that allow each point to contribute to one or more maps
depending on similarity relationships in the original data. This
implementation is a port of the original 'Matlab' library by Laurens van der
Maaten.
See Van der Maaten and Hinton (2012) <doi:10.1007/s10994-011-5273-4>.
This material is based upon work supported by the United States Air Force
and Defense Advanced Research Project Agency (DARPA) under Contract No.
FA8750-17-C-0020.
Any opinions, findings and conclusions or recommendations expressed in this
material are those of the author(s) and do not necessarily reflect the views
of the United States Air Force and Defense Advanced Research Projects Agency.
Distribution Statement A: Approved for Public Release; Distribution Unlimited.

hbeta: Estimate perplexity and probability values

Description

Usage

Arguments