optimize_embedding

matrix with embedding coordinates 
(This should be transpose of final embedding, with coordinates along columns, items in rows)

embedding

matrix with two columns; rows should linke to (from, to); indexes 0-based

pairs

numeric vector, epochs for next sample

numeric vector, epochs for next negative sample

epns

vector with configuration parameters, a, b, gamma, move_other

alpha0

run a series of epochs of the umap optimization

internal

Uniform manifold approximation and projection is a technique
for dimension reduction. The algorithm was described by McInnes and
Healy (2018) in <arXiv:1802.03426>. This package provides an interface
for two implementations. One is written from scratch, including components
for nearest-neighbor search and for embedding. The second implementation
is a wrapper for 'python' package 'umap-learn' (requires separate
installation, see vignette for more details).

optimize_embedding: run a series of epochs of the umap optimization

Description

Usage

Arguments