\section{/var/www/mlpack.ratml.\+org/mlpack.org/\+\_\+src/mlpack-\/3.3.1/src/mlpack/methods/amf/amf.hpp File Reference}
\label{amf_8hpp}\index{/var/www/mlpack.\+ratml.\+org/mlpack.\+org/\+\_\+src/mlpack-\/3.\+3.\+1/src/mlpack/methods/amf/amf.\+hpp@{/var/www/mlpack.\+ratml.\+org/mlpack.\+org/\+\_\+src/mlpack-\/3.\+3.\+1/src/mlpack/methods/amf/amf.\+hpp}}
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\subsection*{Classes}
\begin{DoxyCompactItemize}
\item 
class \textbf{ A\+M\+F$<$ Termination\+Policy\+Type, Initialization\+Rule\+Type, Update\+Rule\+Type $>$}
\begin{DoxyCompactList}\small\item\em This class implements \doxyref{A\+MF}{p.}{classmlpack_1_1amf_1_1AMF} (alternating matrix factorization) on the given matrix V. \end{DoxyCompactList}\end{DoxyCompactItemize}
\subsection*{Namespaces}
\begin{DoxyCompactItemize}
\item 
 \textbf{ mlpack}
\begin{DoxyCompactList}\small\item\em strip\+\_\+type.\+hpp \end{DoxyCompactList}\item 
 \textbf{ mlpack\+::amf}
\begin{DoxyCompactList}\small\item\em Alternating Matrix Factorization. \end{DoxyCompactList}\end{DoxyCompactItemize}
\subsection*{Typedefs}
\begin{DoxyCompactItemize}
\item 
typedef amf\+::\+A\+MF$<$ amf\+::\+Simple\+Residue\+Termination, amf\+::\+Random\+Acol\+Initialization$<$$>$, amf\+::\+N\+M\+F\+A\+L\+S\+Update $>$ \textbf{ N\+M\+F\+A\+L\+S\+Factorizer}
\item 
{\footnotesize template$<$typename Mat\+Type  = arma\+::mat$>$ }\\using \textbf{ S\+V\+D\+Batch\+Factorizer} = amf\+::\+A\+MF$<$ amf\+::\+Simple\+Residue\+Termination, amf\+::\+Random\+Acol\+Initialization$<$$>$, amf\+::\+S\+V\+D\+Batch\+Learning $>$
\begin{DoxyCompactList}\small\item\em Convenience typedefs. \end{DoxyCompactList}\item 
{\footnotesize template$<$class Mat\+Type  = arma\+::mat$>$ }\\using \textbf{ S\+V\+D\+Complete\+Incremental\+Factorizer} = amf\+::\+A\+MF$<$ amf\+::\+Simple\+Residue\+Termination, amf\+::\+Random\+Acol\+Initialization$<$$>$, amf\+::\+S\+V\+D\+Complete\+Incremental\+Learning$<$ Mat\+Type $>$ $>$
\begin{DoxyCompactList}\small\item\em S\+V\+D\+Complete\+Incremental\+Factorizer factorizes given matrix V into two matrices W and H by complete incremental gradient descent. \end{DoxyCompactList}\item 
{\footnotesize template$<$class Mat\+Type  = arma\+::mat$>$ }\\using \textbf{ S\+V\+D\+Incomplete\+Incremental\+Factorizer} = amf\+::\+A\+MF$<$ amf\+::\+Simple\+Residue\+Termination, amf\+::\+Random\+Acol\+Initialization$<$$>$, amf\+::\+S\+V\+D\+Incomplete\+Incremental\+Learning $>$
\begin{DoxyCompactList}\small\item\em S\+V\+D\+Incomplete\+Incremental\+Factorizer factorizes given matrix V into two matrices W and H by incomplete incremental gradient descent. \end{DoxyCompactList}\end{DoxyCompactItemize}


\subsection{Detailed Description}
\begin{DoxyAuthor}{Author}
Sumedh Ghaisas 

Mohan Rajendran 

Ryan Curtin
\end{DoxyAuthor}
Alternating Matrix Factorization

The A\+MF (alternating matrix factorization) class, from which more commonly known techniques such as incremental S\+VD, N\+MF, and batch-\/learning S\+VD can be derived.

mlpack is free software; you may redistribute it and/or modify it under the terms of the 3-\/clause B\+SD license. You should have received a copy of the 3-\/clause B\+SD license along with mlpack. If not, see {\tt http\+://www.\+opensource.\+org/licenses/\+B\+S\+D-\/3-\/\+Clause} for more information. 