\section{Kernel\+Traits$<$ Kernel\+Type $>$ Class Template Reference}
\label{classmlpack_1_1kernel_1_1KernelTraits}\index{Kernel\+Traits$<$ Kernel\+Type $>$@{Kernel\+Traits$<$ Kernel\+Type $>$}}


This is a template class that can provide information about various kernels.  


\subsection*{Static Public Attributes}
\begin{DoxyCompactItemize}
\item 
static const bool \textbf{ Is\+Normalized} = false
\begin{DoxyCompactList}\small\item\em If true, then the kernel is normalized\+: K(x, x) = K(y, y) = 1 for all x. \end{DoxyCompactList}\item 
static const bool \textbf{ Uses\+Squared\+Distance} = false
\begin{DoxyCompactList}\small\item\em If true, then the kernel include a squared distance, $\vert$$\vert$x -\/ y$\vert$$\vert$$^\wedge$2 . \end{DoxyCompactList}\end{DoxyCompactItemize}


\subsection{Detailed Description}
\subsubsection*{template$<$typename Kernel\+Type$>$\newline
class mlpack\+::kernel\+::\+Kernel\+Traits$<$ Kernel\+Type $>$}

This is a template class that can provide information about various kernels. 

By default, this class will provide the weakest possible assumptions on kernels, and each kernel should override values as necessary. If a kernel doesn\textquotesingle{}t need to override a value, then there\textquotesingle{}s no need to write a \doxyref{Kernel\+Traits}{p.}{classmlpack_1_1kernel_1_1KernelTraits} specialization for that class. 

Definition at line 27 of file kernel\+\_\+traits.\+hpp.



\subsection{Member Data Documentation}
\mbox{\label{classmlpack_1_1kernel_1_1KernelTraits_a213c74e1e7c01890b64c8b9e88f8c0dc}} 
\index{mlpack\+::kernel\+::\+Kernel\+Traits@{mlpack\+::kernel\+::\+Kernel\+Traits}!Is\+Normalized@{Is\+Normalized}}
\index{Is\+Normalized@{Is\+Normalized}!mlpack\+::kernel\+::\+Kernel\+Traits@{mlpack\+::kernel\+::\+Kernel\+Traits}}
\subsubsection{Is\+Normalized}
{\footnotesize\ttfamily const bool Is\+Normalized = false\hspace{0.3cm}{\ttfamily [static]}}



If true, then the kernel is normalized\+: K(x, x) = K(y, y) = 1 for all x. 



Definition at line 33 of file kernel\+\_\+traits.\+hpp.

\mbox{\label{classmlpack_1_1kernel_1_1KernelTraits_a12fc177e124e69c8efbac5b08e5c5196}} 
\index{mlpack\+::kernel\+::\+Kernel\+Traits@{mlpack\+::kernel\+::\+Kernel\+Traits}!Uses\+Squared\+Distance@{Uses\+Squared\+Distance}}
\index{Uses\+Squared\+Distance@{Uses\+Squared\+Distance}!mlpack\+::kernel\+::\+Kernel\+Traits@{mlpack\+::kernel\+::\+Kernel\+Traits}}
\subsubsection{Uses\+Squared\+Distance}
{\footnotesize\ttfamily const bool Uses\+Squared\+Distance = false\hspace{0.3cm}{\ttfamily [static]}}



If true, then the kernel include a squared distance, $\vert$$\vert$x -\/ y$\vert$$\vert$$^\wedge$2 . 



Definition at line 38 of file kernel\+\_\+traits.\+hpp.



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.\+0/src/mlpack/core/kernels/\textbf{ kernel\+\_\+traits.\+hpp}\end{DoxyCompactItemize}
