print.poismf

Print basic properties of a "poismf" object.

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.

David Cortes

poismf

Factorization of Sparse Counts Matrices Through Poisson
Likelihood

Jean-Sebastien Roy

Stephen Nash

print.poismf function

<dl><dt>x</dt>
<dd>An object of class "poismf" as returned by function "poismf".</dd>
<dt>...</dt>
<dd>Extra arguments (not used).</dd></dl>

Arguments

Get information about poismf object — print.poismf

<dl>

<dt>x</dt>
<dd>An object of class "poismf" as returned by function "poismf".</dd>


<dt>...</dt>
<dd>Extra arguments (not used).</dd>

</dl>

print.poismf: Get information about poismf object

Description

Usage

Arguments