Package: poismf
Type: Package
Title: Factorization of Sparse Counts Matrices Through Poisson Likelihood
Version: 0.1.4
Date: 2019-09-03
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>
URL: https://github.com/david-cortes/poismf
BugReports: https://github.com/david-cortes/poismf/issues
Description: Creates a low-rank factorization of a sparse counts matrix by maximizing Poisson likelihood with l1/l2 regularization
	with all non-negative latent factors (e.g. for recommender systems or topic modeling) (Cortes, (2018) <arXiv:1811.01908>).
	Similar to hierarchical Poisson factorization, but follows an optimization-based approach with regularization instead of a hierarchical
	structure, and is fit through either proximal gradient or conjugate gradient instead of variational inference.
License: BSD_2_clause + file LICENSE
Imports: Rcpp (>= 0.12.19), Matrix, methods, nonneg.cg
Enhances: SparseM
LinkingTo: Rcpp
RoxygenNote: 6.1.1
NeedsCompilation: yes
