DESCRIPTION

Package: poismf
Type: Package
Title: Factorization of Sparse Counts Matrices Through Poisson Likelihood
Version: 0.4.0-3
Authors@R: c(
  person(given="David", family="Cortes", role=c("aut", "cre", "cph"),
         email="david.cortes.rivera@gmail.com"),
  person(given="Jean-Sebastien", family="Roy", role="cph",
         comment="Copyright holder of included tnc library"),
  person(given="Stephen", family="Nash", role="cph",
         comment="Copyright holder of included tnc library")
  )
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 non-negative low-rank approximate factorization of a sparse counts matrix by maximizing Poisson
    likelihood with L1/L2 regularization (e.g. for implicit-feedback recommender systems or bag-of-words-based topic modeling)
    (Cortes, (2018) <arXiv:1811.01908>), which usually leads to very sparse user and item factors (over 90% zero-valued).
    Similar to hierarchical Poisson factorization (HPF), but follows an optimization-based approach with regularization
    instead of a hierarchical prior, and is fit through gradient-based methods instead of variational inference.
License: BSD_2_clause + file LICENSE
Imports: Matrix (>= 1.3), methods
RoxygenNote: 7.2.1
NeedsCompilation: yes
Encoding: UTF-8