nnTensor: An R package for non-negative matrix/tensor decomposition

Peer-reviewed software and manuscript. See the JOSS review issue for details:
openjournals/joss-reviews#5015

Non-negative matrix factorization (NMF) is a widely used algorithm to decompose non-negative matrix data into factor matrices. Due to the interpretability of its non-negativity and the convenience of using decomposition results as clustering, there are many applications of NMF in image processing, audio processing, and bioinformatics.

NMF has been applied to matrix data but there is a growing demand to apply NMF to more heterogeneous non-negative data such as multiple matrices and tensors (high-dimensional arrays), which are higher-order data structures than matrices. To meet these requirements, we originally developed nnTensor, which is an R/CRAN package to perform some non-negative matrix/tensor decomposition algorithms (https://cran.r-project.org/web/packages/nnTensor/index.html).

Zenodo doi: 10.5281/zenodo.7848088