\section{Dual\+Tree\+K\+Means$<$ Metric\+Type, Mat\+Type, Tree\+Type $>$ Class Template Reference}
\label{classmlpack_1_1kmeans_1_1DualTreeKMeans}\index{Dual\+Tree\+K\+Means$<$ Metric\+Type, Mat\+Type, Tree\+Type $>$@{Dual\+Tree\+K\+Means$<$ Metric\+Type, Mat\+Type, Tree\+Type $>$}}


An algorithm for an exact Lloyd iteration which simply uses dual-\/tree nearest-\/neighbor search to find the nearest centroid for each point in the dataset.  


\subsection*{Public Types}
\begin{DoxyCompactItemize}
\item 
{\footnotesize template$<$typename Tree\+Metric\+Type , typename Ignored\+Stat\+Type , typename Tree\+Mat\+Type $>$ }\\using \textbf{ N\+N\+S\+Tree\+Type} = Tree\+Type$<$ Tree\+Metric\+Type, \textbf{ Dual\+Tree\+K\+Means\+Statistic}, Tree\+Mat\+Type $>$
\item 
typedef Tree\+Type$<$ Metric\+Type, \textbf{ Dual\+Tree\+K\+Means\+Statistic}, Mat\+Type $>$ \textbf{ Tree}
\begin{DoxyCompactList}\small\item\em Convenience typedef. \end{DoxyCompactList}\end{DoxyCompactItemize}
\subsection*{Public Member Functions}
\begin{DoxyCompactItemize}
\item 
\textbf{ Dual\+Tree\+K\+Means} (const Mat\+Type \&dataset, Metric\+Type \&metric)
\begin{DoxyCompactList}\small\item\em Construct the \doxyref{Dual\+Tree\+K\+Means}{p.}{classmlpack_1_1kmeans_1_1DualTreeKMeans} object, which will construct a tree on the points. \end{DoxyCompactList}\item 
\textbf{ $\sim$\+Dual\+Tree\+K\+Means} ()
\begin{DoxyCompactList}\small\item\em Delete the tree constructed by the \doxyref{Dual\+Tree\+K\+Means}{p.}{classmlpack_1_1kmeans_1_1DualTreeKMeans} object. \end{DoxyCompactList}\item 
size\+\_\+t \textbf{ Distance\+Calculations} () const
\begin{DoxyCompactList}\small\item\em Return the number of distance calculations. \end{DoxyCompactList}\item 
size\+\_\+t \& \textbf{ Distance\+Calculations} ()
\begin{DoxyCompactList}\small\item\em Modify the number of distance calculations. \end{DoxyCompactList}\item 
double \textbf{ Iterate} (const arma\+::mat \&centroids, arma\+::mat \&new\+Centroids, arma\+::\+Col$<$ size\+\_\+t $>$ \&counts)
\begin{DoxyCompactList}\small\item\em Run a single iteration of the dual-\/tree nearest neighbor algorithm for k-\/means, updating the given centroids into the new\+Centroids matrix. \end{DoxyCompactList}\end{DoxyCompactItemize}


\subsection{Detailed Description}
\subsubsection*{template$<$typename Metric\+Type, typename Mat\+Type, template$<$ typename Tree\+Metric\+Type, typename Tree\+Stat\+Type, typename Tree\+Mat\+Type $>$ class Tree\+Type = tree\+::\+K\+D\+Tree$>$\newline
class mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means$<$ Metric\+Type, Mat\+Type, Tree\+Type $>$}

An algorithm for an exact Lloyd iteration which simply uses dual-\/tree nearest-\/neighbor search to find the nearest centroid for each point in the dataset. 

The conditions under which this will perform best are probably limited to the case where k is close to the number of points in the dataset, and the number of iterations of the k-\/means algorithm will be few. 

Definition at line 41 of file dual\+\_\+tree\+\_\+kmeans.\+hpp.



\subsection{Member Typedef Documentation}
\mbox{\label{classmlpack_1_1kmeans_1_1DualTreeKMeans_a5b3ef294d06f18f1075d54975f0e7aad}} 
\index{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}!N\+N\+S\+Tree\+Type@{N\+N\+S\+Tree\+Type}}
\index{N\+N\+S\+Tree\+Type@{N\+N\+S\+Tree\+Type}!mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}}
\subsubsection{N\+N\+S\+Tree\+Type}
{\footnotesize\ttfamily using \textbf{ N\+N\+S\+Tree\+Type} =  Tree\+Type$<$Tree\+Metric\+Type, \textbf{ Dual\+Tree\+K\+Means\+Statistic}, Tree\+Mat\+Type$>$}



Definition at line 51 of file dual\+\_\+tree\+\_\+kmeans.\+hpp.

\mbox{\label{classmlpack_1_1kmeans_1_1DualTreeKMeans_acaad795a6a26818330dd2476ec5e8731}} 
\index{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}!Tree@{Tree}}
\index{Tree@{Tree}!mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}}
\subsubsection{Tree}
{\footnotesize\ttfamily typedef Tree\+Type$<$Metric\+Type, \textbf{ Dual\+Tree\+K\+Means\+Statistic}, Mat\+Type$>$ \textbf{ Tree}}



Convenience typedef. 



Definition at line 45 of file dual\+\_\+tree\+\_\+kmeans.\+hpp.



\subsection{Constructor \& Destructor Documentation}
\mbox{\label{classmlpack_1_1kmeans_1_1DualTreeKMeans_a6c9ca881ce3156575e49ee41509c9e84}} 
\index{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}!Dual\+Tree\+K\+Means@{Dual\+Tree\+K\+Means}}
\index{Dual\+Tree\+K\+Means@{Dual\+Tree\+K\+Means}!mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}}
\subsubsection{Dual\+Tree\+K\+Means()}
{\footnotesize\ttfamily \textbf{ Dual\+Tree\+K\+Means} (\begin{DoxyParamCaption}\item[{const Mat\+Type \&}]{dataset,  }\item[{Metric\+Type \&}]{metric }\end{DoxyParamCaption})}



Construct the \doxyref{Dual\+Tree\+K\+Means}{p.}{classmlpack_1_1kmeans_1_1DualTreeKMeans} object, which will construct a tree on the points. 

\mbox{\label{classmlpack_1_1kmeans_1_1DualTreeKMeans_a41aea8db220102203364a89819766541}} 
\index{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}!````~Dual\+Tree\+K\+Means@{$\sim$\+Dual\+Tree\+K\+Means}}
\index{````~Dual\+Tree\+K\+Means@{$\sim$\+Dual\+Tree\+K\+Means}!mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}}
\subsubsection{$\sim$\+Dual\+Tree\+K\+Means()}
{\footnotesize\ttfamily $\sim$\textbf{ Dual\+Tree\+K\+Means} (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})}



Delete the tree constructed by the \doxyref{Dual\+Tree\+K\+Means}{p.}{classmlpack_1_1kmeans_1_1DualTreeKMeans} object. 



\subsection{Member Function Documentation}
\mbox{\label{classmlpack_1_1kmeans_1_1DualTreeKMeans_a6ab05a40f496b49e405530a1d39120ef}} 
\index{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}!Distance\+Calculations@{Distance\+Calculations}}
\index{Distance\+Calculations@{Distance\+Calculations}!mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}}
\subsubsection{Distance\+Calculations()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}}
{\footnotesize\ttfamily size\+\_\+t Distance\+Calculations (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}}



Return the number of distance calculations. 



Definition at line 77 of file dual\+\_\+tree\+\_\+kmeans.\+hpp.

\mbox{\label{classmlpack_1_1kmeans_1_1DualTreeKMeans_a7fd6d18544595d62025c4b740f8664ab}} 
\index{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}!Distance\+Calculations@{Distance\+Calculations}}
\index{Distance\+Calculations@{Distance\+Calculations}!mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}}
\subsubsection{Distance\+Calculations()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}}
{\footnotesize\ttfamily size\+\_\+t\& Distance\+Calculations (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}}



Modify the number of distance calculations. 



Definition at line 79 of file dual\+\_\+tree\+\_\+kmeans.\+hpp.



References mlpack\+::kmeans\+::\+Hide\+Child(), and mlpack\+::kmeans\+::\+Restore\+Children().

\mbox{\label{classmlpack_1_1kmeans_1_1DualTreeKMeans_a1618db5fb0d2893a50f0c8614d970453}} 
\index{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}!Iterate@{Iterate}}
\index{Iterate@{Iterate}!mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means@{mlpack\+::kmeans\+::\+Dual\+Tree\+K\+Means}}
\subsubsection{Iterate()}
{\footnotesize\ttfamily double Iterate (\begin{DoxyParamCaption}\item[{const arma\+::mat \&}]{centroids,  }\item[{arma\+::mat \&}]{new\+Centroids,  }\item[{arma\+::\+Col$<$ size\+\_\+t $>$ \&}]{counts }\end{DoxyParamCaption})}



Run a single iteration of the dual-\/tree nearest neighbor algorithm for k-\/means, updating the given centroids into the new\+Centroids matrix. 


\begin{DoxyParams}{Parameters}
{\em centroids} & Current cluster centroids. \\
\hline
{\em new\+Centroids} & New cluster centroids. \\
\hline
{\em counts} & Current counts, to be overwritten with new counts. \\
\hline
\end{DoxyParams}


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/methods/kmeans/\textbf{ dual\+\_\+tree\+\_\+kmeans.\+hpp}\end{DoxyCompactItemize}
