\section{Sigmoid\+Cross\+Entropy\+Error$<$ Input\+Data\+Type, Output\+Data\+Type $>$ Class Template Reference} \label{classmlpack_1_1ann_1_1SigmoidCrossEntropyError}\index{Sigmoid\+Cross\+Entropy\+Error$<$ Input\+Data\+Type, Output\+Data\+Type $>$@{Sigmoid\+Cross\+Entropy\+Error$<$ Input\+Data\+Type, Output\+Data\+Type $>$}} The \doxyref{Sigmoid\+Cross\+Entropy\+Error}{p.}{classmlpack_1_1ann_1_1SigmoidCrossEntropyError} performance function measures the network\textquotesingle{}s performance according to the cross-\/entropy function between the input and target distributions. \subsection*{Public Member Functions} \begin{DoxyCompactItemize} \item \textbf{ Sigmoid\+Cross\+Entropy\+Error} () \begin{DoxyCompactList}\small\item\em Create the \doxyref{Sigmoid\+Cross\+Entropy\+Error}{p.}{classmlpack_1_1ann_1_1SigmoidCrossEntropyError} object. \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 Sigmoid Cross\+Entropy Error functions. \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\+::\+Sigmoid\+Cross\+Entropy\+Error$<$ Input\+Data\+Type, Output\+Data\+Type $>$} The \doxyref{Sigmoid\+Cross\+Entropy\+Error}{p.}{classmlpack_1_1ann_1_1SigmoidCrossEntropyError} performance function measures the network\textquotesingle{}s performance according to the cross-\/entropy function between the input and target distributions. This function calculates the cross entropy given the real values instead of providing the sigmoid activations. The function uses this equivalent formulation\+: $max(x, 0) - x * z + \log(1 + e^{-|x|})$ where x = input and z = target. For more information, see the following paper. \begin{DoxyCode} @article\{Janocha2017 title = \{On Loss Functions \textcolor{keywordflow}{for} Deep Neural Networks in Classification\}, author = \{Katarzyna Janocha, Wojciech Marian Czarnecki\}, url = \{http:\textcolor{comment}{//arxiv.org/abs/1702.05659\},} journal = \{CoRR\}, eprint = \{arXiv:1702.05659\}, year = \{2017\} \} \end{DoxyCode} \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 52 of file sigmoid\+\_\+cross\+\_\+entropy\+\_\+error.\+hpp. \subsection{Constructor \& Destructor Documentation} \mbox{\label{classmlpack_1_1ann_1_1SigmoidCrossEntropyError_a5d08bab32a040d5a35d277ed020930a1}} \index{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}!Sigmoid\+Cross\+Entropy\+Error@{Sigmoid\+Cross\+Entropy\+Error}} \index{Sigmoid\+Cross\+Entropy\+Error@{Sigmoid\+Cross\+Entropy\+Error}!mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}} \subsubsection{Sigmoid\+Cross\+Entropy\+Error()} {\footnotesize\ttfamily \textbf{ Sigmoid\+Cross\+Entropy\+Error} (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})} Create the \doxyref{Sigmoid\+Cross\+Entropy\+Error}{p.}{classmlpack_1_1ann_1_1SigmoidCrossEntropyError} object. \subsection{Member Function Documentation} \mbox{\label{classmlpack_1_1ann_1_1SigmoidCrossEntropyError_a7a5e88245fe9cf5644f846902393e97a}} \index{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}!Backward@{Backward}} \index{Backward@{Backward}!mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}} \subsubsection{Backward()} {\footnotesize\ttfamily void Backward (\begin{DoxyParamCaption}\item[{const Input\+Type \&}]{input, }\item[{const Target\+Type \&}]{target, }\item[{Output\+Type \&}]{output }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Ordinary feed backward pass of a neural network. \begin{DoxyParams}{Parameters} {\em input} & The propagated input activation. \\ \hline {\em target} & The target vector. \\ \hline {\em output} & The calculated error. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1ann_1_1SigmoidCrossEntropyError_aad9536a75d4ecfe220d313adc47f38fa}} \index{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}!Forward@{Forward}} \index{Forward@{Forward}!mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}} \subsubsection{Forward()} {\footnotesize\ttfamily Input\+Type\+::elem\+\_\+type Forward (\begin{DoxyParamCaption}\item[{const Input\+Type \&}]{input, }\item[{const Target\+Type \&}]{target }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Computes the Sigmoid Cross\+Entropy Error functions. \begin{DoxyParams}{Parameters} {\em input} & Input data used for evaluating the specified function. \\ \hline {\em target} & The target vector. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1ann_1_1SigmoidCrossEntropyError_a8bae962cc603d1cab8d80ec78f8d505d}} \index{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}} \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 82 of file sigmoid\+\_\+cross\+\_\+entropy\+\_\+error.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1SigmoidCrossEntropyError_a21d5f745f02c709625a4ee0907f004a5}} \index{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}} \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 84 of file sigmoid\+\_\+cross\+\_\+entropy\+\_\+error.\+hpp. References Sigmoid\+Cross\+Entropy\+Error$<$ Input\+Data\+Type, Output\+Data\+Type $>$\+::serialize(). \mbox{\label{classmlpack_1_1ann_1_1SigmoidCrossEntropyError_af0dd9205158ccf7bcfcd8ff81f79c927}} \index{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}!serialize@{serialize}} \index{serialize@{serialize}!mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error@{mlpack\+::ann\+::\+Sigmoid\+Cross\+Entropy\+Error}} \subsubsection{serialize()} {\footnotesize\ttfamily void serialize (\begin{DoxyParamCaption}\item[{Archive \&}]{ar, }\item[{const unsigned}]{int }\end{DoxyParamCaption})} Serialize the layer. Referenced by Sigmoid\+Cross\+Entropy\+Error$<$ Input\+Data\+Type, Output\+Data\+Type $>$\+::\+Output\+Parameter(). 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{ sigmoid\+\_\+cross\+\_\+entropy\+\_\+error.\+hpp}\end{DoxyCompactItemize}