R: Hierarchical Non-Negative Matrix Factorization

# Hierarchical Non-Negative Matrix Factorization

## Documentation for package ‘hNMF’ version 1.0

- DESCRIPTION file

## Help Pages

HALSacc | Accelerated hierarchical alternating least squares NMF. For a reference to the method, see N. Gillis, Nonnegative matrix factorization: complexity, algorithms and applications [Section 4.2, Algo. 6], PhD thesis, Université catholique de Louvain, February 2011.
hNMF | Hierarchical non-negative matrix factorization.
imoverlay | Overlay a mask or a color scaled image on top of a background image
initializeNMF | Initialize NMF model with initial spectral data
initializeSPA | The successive projection algorithm, a useful method for initializing the NMF source matrix
oneLevelNMF | Perform Non-Negative Matrix factorization
PGNMF | NMF by alternating non-negative least squares using projected gradients. For a reference to the method, see C.-J. Lin, "Projected Gradient Methods for Non-negative Matrix Factorization", Neural computation 19.10 (2007): 2756-2779.
preProcesInputData | Condition input data matrix properly for NMF
residualNMF | Computation of relative NMF residual per observation
scaleNMFResult | Apply fixed scaling to NMF model matrices by normalizing the basis vectors
semiNMF | Semi-NMF based on multiplicative update rules. Reference: C. Ding, T. Li, and M.I. Jordan, "Convex and semi-nonnegative matrix factorizations", IEEE Transations on Pattern Analysis and Machine Intelligence, vol. 32, no. 1, pp. 45-55, 2010.