Package: poismf
Type: Package
Title: Factorization of Sparse Counts Matrices Through Poisson
        Likelihood
Version: 0.4.0-4
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: 7.1.2
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2023-03-26 14:41:07 UTC; david
Author: David Cortes [aut, cre, cph],
  Jean-Sebastien Roy [cph] (Copyright holder of included tnc library),
  Stephen Nash [cph] (Copyright holder of included tnc library)
Repository: CRAN
Date/Publication: 2023-03-26 21:30:02 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 01:32:50 UTC; unix
Archs: poismf.so.dSYM
