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