\section{Margin\+Ranking\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$ Class Template Reference} \label{classmlpack_1_1ann_1_1MarginRankingLoss}\index{Margin\+Ranking\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$@{Margin\+Ranking\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$}} Margin ranking loss measures the loss given inputs and a label vector with values of 1 or -\/1. \subsection*{Public Member Functions} \begin{DoxyCompactItemize} \item \textbf{ Margin\+Ranking\+Loss} (const double margin=1.\+0) \begin{DoxyCompactList}\small\item\em Create the \doxyref{Margin\+Ranking\+Loss}{p.}{classmlpack_1_1ann_1_1MarginRankingLoss} object with Hyperparameter margin. \end{DoxyCompactList}\item {\footnotesize template$<$typename Input\+Type , typename Target\+Type , typename Output\+Type $>$ }\\void \textbf{ Backward} (const Input\+Type \&input, const Target\+Type \&target, Output\+Type \&output) \begin{DoxyCompactList}\small\item\em Ordinary feed backward pass of a neural network. \end{DoxyCompactList}\item {\footnotesize template$<$typename Input\+Type , typename Target\+Type $>$ }\\Input\+Type\+::elem\+\_\+type \textbf{ Forward} (const Input\+Type \&input, const Target\+Type \&target) \begin{DoxyCompactList}\small\item\em Computes the Margin Ranking Loss function. \end{DoxyCompactList}\item double \textbf{ Margin} () const \begin{DoxyCompactList}\small\item\em Get the margin parameter. \end{DoxyCompactList}\item double \& \textbf{ Margin} () \begin{DoxyCompactList}\small\item\em Modify the margin parameter. \end{DoxyCompactList}\item Output\+Data\+Type \& \textbf{ Output\+Parameter} () const \begin{DoxyCompactList}\small\item\em Get the output parameter. \end{DoxyCompactList}\item Output\+Data\+Type \& \textbf{ Output\+Parameter} () \begin{DoxyCompactList}\small\item\em Modify the output parameter. \end{DoxyCompactList}\item {\footnotesize template$<$typename Archive $>$ }\\void \textbf{ serialize} (Archive \&ar, const unsigned int) \begin{DoxyCompactList}\small\item\em Serialize the layer. \end{DoxyCompactList}\end{DoxyCompactItemize} \subsection{Detailed Description} \subsubsection*{template$<$typename Input\+Data\+Type = arma\+::mat, typename Output\+Data\+Type = arma\+::mat$>$\newline class mlpack\+::ann\+::\+Margin\+Ranking\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$} Margin ranking loss measures the loss given inputs and a label vector with values of 1 or -\/1. If the label is 1 then the first input should be ranked higher than the second input at a distance larger than a margin, and vice-\/ versa if the label is -\/1. \begin{DoxyTemplParams}{Template Parameters} {\em Input\+Data\+Type} & Type of the input data (arma\+::colvec, arma\+::mat, arma\+::sp\+\_\+mat or arma\+::cube). \\ \hline {\em Output\+Data\+Type} & Type of the output data (arma\+::colvec, arma\+::mat, arma\+::sp\+\_\+mat or arma\+::cube). \\ \hline \end{DoxyTemplParams} Definition at line 35 of file margin\+\_\+ranking\+\_\+loss.\+hpp. \subsection{Constructor \& Destructor Documentation} \mbox{\label{classmlpack_1_1ann_1_1MarginRankingLoss_a28d56cfc63a5a75cd5479f335c65df0c}} \index{mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}!Margin\+Ranking\+Loss@{Margin\+Ranking\+Loss}} \index{Margin\+Ranking\+Loss@{Margin\+Ranking\+Loss}!mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}} \subsubsection{Margin\+Ranking\+Loss()} {\footnotesize\ttfamily \textbf{ Margin\+Ranking\+Loss} (\begin{DoxyParamCaption}\item[{const double}]{margin = {\ttfamily 1.0} }\end{DoxyParamCaption})} Create the \doxyref{Margin\+Ranking\+Loss}{p.}{classmlpack_1_1ann_1_1MarginRankingLoss} object with Hyperparameter margin. Hyperparameter margin defines a minimum distance between correctly ranked samples. \subsection{Member Function Documentation} \mbox{\label{classmlpack_1_1ann_1_1MarginRankingLoss_a7a5e88245fe9cf5644f846902393e97a}} \index{mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}!Backward@{Backward}} \index{Backward@{Backward}!mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}} \subsubsection{Backward()} {\footnotesize\ttfamily void Backward (\begin{DoxyParamCaption}\item[{const Input\+Type \&}]{input, }\item[{const Target\+Type \&}]{target, }\item[{Output\+Type \&}]{output }\end{DoxyParamCaption})} Ordinary feed backward pass of a neural network. \begin{DoxyParams}{Parameters} {\em input} & The propagated concatenated input activation. \\ \hline {\em target} & The label vector which contains -\/1 or 1 values. \\ \hline {\em output} & The calculated error. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1ann_1_1MarginRankingLoss_aad9536a75d4ecfe220d313adc47f38fa}} \index{mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}!Forward@{Forward}} \index{Forward@{Forward}!mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}} \subsubsection{Forward()} {\footnotesize\ttfamily Input\+Type\+::elem\+\_\+type Forward (\begin{DoxyParamCaption}\item[{const Input\+Type \&}]{input, }\item[{const Target\+Type \&}]{target }\end{DoxyParamCaption})} Computes the Margin Ranking Loss function. \begin{DoxyParams}{Parameters} {\em input} & Concatenation of the two inputs for evaluating the specified function. \\ \hline {\em target} & The label vector which contains values of -\/1 or 1. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1ann_1_1MarginRankingLoss_ac29c2c851ff367f45f9ec075352c5b83}} \index{mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}!Margin@{Margin}} \index{Margin@{Margin}!mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}} \subsubsection{Margin()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily double Margin (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the margin parameter. Definition at line 78 of file margin\+\_\+ranking\+\_\+loss.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1MarginRankingLoss_ab8c4d252f686cdc9c5972df28e65dcab}} \index{mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}!Margin@{Margin}} \index{Margin@{Margin}!mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}} \subsubsection{Margin()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily double\& Margin (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the margin parameter. Definition at line 80 of file margin\+\_\+ranking\+\_\+loss.\+hpp. References Margin\+Ranking\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$\+::serialize(). \mbox{\label{classmlpack_1_1ann_1_1MarginRankingLoss_a8bae962cc603d1cab8d80ec78f8d505d}} \index{mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}} \subsubsection{Output\+Parameter()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily Output\+Data\+Type\& Output\+Parameter (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the output parameter. Definition at line 73 of file margin\+\_\+ranking\+\_\+loss.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1MarginRankingLoss_a21d5f745f02c709625a4ee0907f004a5}} \index{mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}} \subsubsection{Output\+Parameter()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily Output\+Data\+Type\& Output\+Parameter (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the output parameter. Definition at line 75 of file margin\+\_\+ranking\+\_\+loss.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1MarginRankingLoss_af0dd9205158ccf7bcfcd8ff81f79c927}} \index{mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}!serialize@{serialize}} \index{serialize@{serialize}!mlpack\+::ann\+::\+Margin\+Ranking\+Loss@{mlpack\+::ann\+::\+Margin\+Ranking\+Loss}} \subsubsection{serialize()} {\footnotesize\ttfamily void serialize (\begin{DoxyParamCaption}\item[{Archive \&}]{ar, }\item[{const unsigned}]{int }\end{DoxyParamCaption})} Serialize the layer. Referenced by Margin\+Ranking\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$\+::\+Margin(). The documentation for this class was generated from the following file\+:\begin{DoxyCompactItemize} \item /var/www/mlpack.\+ratml.\+org/mlpack.\+org/\+\_\+src/mlpack-\/3.\+3.\+1/src/mlpack/methods/ann/loss\+\_\+functions/\textbf{ margin\+\_\+ranking\+\_\+loss.\+hpp}\end{DoxyCompactItemize}