The `nmfbin`

R package provides a simple Non-Negative Matrix Factorization (NMF) implementation tailored for binary data matrices. It offers a choice of initialization methods, loss functions and updating algorithms.

NMF is typically used for reducing high-dimensional matrices into lower (k-) rank ones where *k* is chosen by the user. Given a non-negative matrix *X* of size *m* × *n*, NMF looks for two non-negative matrices *W* (*m* × *k*) and *H* (*k* × *n*), such that:

*X* ≈ *W* × *H*

In topic modelling, if *V* is a word-document matrix then *W* can be interpreted as the word-topic matrix and *H* as the topic-document matrix.

Unlike most other NMF packages, `nmfbin`

is focused on binary (Boolean) data, while keeping the number of dependencies to a minimum. For more information see the website.

## Installation

You can install the development version of `nmfbin`

from GitHub with:

```
# install.packages("remotes")
remotes::install_github("michalovadek/nmfbin")
```