\section{Diagonal\+Gaussian\+Distribution Class Reference} \label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution}\index{Diagonal\+Gaussian\+Distribution@{Diagonal\+Gaussian\+Distribution}} A single multivariate Gaussian distribution with diagonal covariance. \subsection*{Public Member Functions} \begin{DoxyCompactItemize} \item \textbf{ Diagonal\+Gaussian\+Distribution} () \begin{DoxyCompactList}\small\item\em Default constructor, which creates a Gaussian with zero dimension. \end{DoxyCompactList}\item \textbf{ Diagonal\+Gaussian\+Distribution} (const size\+\_\+t dimension) \begin{DoxyCompactList}\small\item\em Create a Gaussian Distribution with zero mean and diagonal covariance with the given dimensionality. \end{DoxyCompactList}\item \textbf{ Diagonal\+Gaussian\+Distribution} (const arma\+::vec \&mean, const arma\+::vec \&covariance) \begin{DoxyCompactList}\small\item\em Create a Gaussian distribution with the given mean and diagonal covariance. \end{DoxyCompactList}\item const arma\+::vec \& \textbf{ Covariance} () const \begin{DoxyCompactList}\small\item\em Return the covariance matrix. \end{DoxyCompactList}\item void \textbf{ Covariance} (const arma\+::vec \&covariance) \begin{DoxyCompactList}\small\item\em Set the covariance matrix. \end{DoxyCompactList}\item void \textbf{ Covariance} (arma\+::vec \&\&covariance) \begin{DoxyCompactList}\small\item\em Set the covariance matrix using move assignment. \end{DoxyCompactList}\item size\+\_\+t \textbf{ Dimensionality} () const \begin{DoxyCompactList}\small\item\em Return the dimensionality of this distribution. \end{DoxyCompactList}\item double \textbf{ Log\+Probability} (const arma\+::vec \&observation) const \begin{DoxyCompactList}\small\item\em Return the log probability of the given observation. \end{DoxyCompactList}\item void \textbf{ Log\+Probability} (const arma\+::mat \&observations, arma\+::vec \&log\+Probabilities) const \begin{DoxyCompactList}\small\item\em Calculate the multivariate Gaussian log probability density function for each data point (column) in the given matrix. \end{DoxyCompactList}\item const arma\+::vec \& \textbf{ Mean} () const \begin{DoxyCompactList}\small\item\em Return the mean. \end{DoxyCompactList}\item arma\+::vec \& \textbf{ Mean} () \begin{DoxyCompactList}\small\item\em Return a modifiable copy of the mean. \end{DoxyCompactList}\item double \textbf{ Probability} (const arma\+::vec \&observation) const \begin{DoxyCompactList}\small\item\em Return the probability of the given observation. \end{DoxyCompactList}\item void \textbf{ Probability} (const arma\+::mat \&x, arma\+::vec \&probabilities) const \begin{DoxyCompactList}\small\item\em Calculate the multivariate Gaussian probability density function for each data point (column) in the given matrix. \end{DoxyCompactList}\item arma\+::vec \textbf{ Random} () const \begin{DoxyCompactList}\small\item\em Return a randomly generated observation according to the probability distribution defined by this object. \end{DoxyCompactList}\item {\footnotesize template$<$typename Archive $>$ }\\void \textbf{ serialize} (Archive \&ar, const unsigned int) \begin{DoxyCompactList}\small\item\em Serialize the distribution. \end{DoxyCompactList}\item void \textbf{ Train} (const arma\+::mat \&observations) \begin{DoxyCompactList}\small\item\em Estimate the Gaussian distribution directly from the given observations. \end{DoxyCompactList}\item void \textbf{ Train} (const arma\+::mat \&observations, const arma\+::vec \&probabilities) \begin{DoxyCompactList}\small\item\em Estimate the Gaussian distribution from the given observations, taking into account the probability of each observation actually being from this distribution. \end{DoxyCompactList}\end{DoxyCompactItemize} \subsection{Detailed Description} A single multivariate Gaussian distribution with diagonal covariance. Definition at line 21 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. \subsection{Constructor \& Destructor Documentation} \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_acdb3a37208d86c70813f6bd57976d91d}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Diagonal\+Gaussian\+Distribution@{Diagonal\+Gaussian\+Distribution}} \index{Diagonal\+Gaussian\+Distribution@{Diagonal\+Gaussian\+Distribution}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Diagonal\+Gaussian\+Distribution()\hspace{0.1cm}{\footnotesize\ttfamily [1/3]}} {\footnotesize\ttfamily \textbf{ Diagonal\+Gaussian\+Distribution} (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Default constructor, which creates a Gaussian with zero dimension. Definition at line 38 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. Referenced by Diagonal\+Gaussian\+Distribution\+::\+Diagonal\+Gaussian\+Distribution(). \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a53c6049f223552c6ed646615def048c8}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Diagonal\+Gaussian\+Distribution@{Diagonal\+Gaussian\+Distribution}} \index{Diagonal\+Gaussian\+Distribution@{Diagonal\+Gaussian\+Distribution}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Diagonal\+Gaussian\+Distribution()\hspace{0.1cm}{\footnotesize\ttfamily [2/3]}} {\footnotesize\ttfamily \textbf{ Diagonal\+Gaussian\+Distribution} (\begin{DoxyParamCaption}\item[{const size\+\_\+t}]{dimension }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Create a Gaussian Distribution with zero mean and diagonal covariance with the given dimensionality. \begin{DoxyParams}{Parameters} {\em dimension} & Number of dimensions. \\ \hline \end{DoxyParams} Definition at line 46 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. References Diagonal\+Gaussian\+Distribution\+::\+Diagonal\+Gaussian\+Distribution(). \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a99d581f05bb370789481f5c33747d616}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Diagonal\+Gaussian\+Distribution@{Diagonal\+Gaussian\+Distribution}} \index{Diagonal\+Gaussian\+Distribution@{Diagonal\+Gaussian\+Distribution}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Diagonal\+Gaussian\+Distribution()\hspace{0.1cm}{\footnotesize\ttfamily [3/3]}} {\footnotesize\ttfamily \textbf{ Diagonal\+Gaussian\+Distribution} (\begin{DoxyParamCaption}\item[{const arma\+::vec \&}]{mean, }\item[{const arma\+::vec \&}]{covariance }\end{DoxyParamCaption})} Create a Gaussian distribution with the given mean and diagonal covariance. \begin{DoxyParams}{Parameters} {\em mean} & Mean of distribution. \\ \hline {\em covariance} & Covariance of distribution. \\ \hline \end{DoxyParams} \subsection{Member Function Documentation} \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_ad6dd9f58ac49805f6c1c4d473880e907}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Covariance@{Covariance}} \index{Covariance@{Covariance}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Covariance()\hspace{0.1cm}{\footnotesize\ttfamily [1/3]}} {\footnotesize\ttfamily const arma\+::vec\& Covariance (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Return the covariance matrix. Definition at line 133 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_ae6f1bf6b3f2bf510f1b37b34ed38bc69}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Covariance@{Covariance}} \index{Covariance@{Covariance}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Covariance()\hspace{0.1cm}{\footnotesize\ttfamily [2/3]}} {\footnotesize\ttfamily void Covariance (\begin{DoxyParamCaption}\item[{const arma\+::vec \&}]{covariance }\end{DoxyParamCaption})} Set the covariance matrix. \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a89b5e71beec8cc65746c402006b1c445}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Covariance@{Covariance}} \index{Covariance@{Covariance}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Covariance()\hspace{0.1cm}{\footnotesize\ttfamily [3/3]}} {\footnotesize\ttfamily void Covariance (\begin{DoxyParamCaption}\item[{arma\+::vec \&\&}]{covariance }\end{DoxyParamCaption})} Set the covariance matrix using move assignment. \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a78eda6bfb9e9462afa0fc85e32abe1af}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Dimensionality@{Dimensionality}} \index{Dimensionality@{Dimensionality}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Dimensionality()} {\footnotesize\ttfamily size\+\_\+t Dimensionality (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Return the dimensionality of this distribution. Definition at line 64 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a7063c1fb92f512f32bf44542c7528739}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Log\+Probability@{Log\+Probability}} \index{Log\+Probability@{Log\+Probability}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Log\+Probability()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily double Log\+Probability (\begin{DoxyParamCaption}\item[{const arma\+::vec \&}]{observation }\end{DoxyParamCaption}) const} Return the log probability of the given observation. Referenced by Diagonal\+Gaussian\+Distribution\+::\+Probability(). \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a10aa8675001ec75323be892d23b4a2cb}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Log\+Probability@{Log\+Probability}} \index{Log\+Probability@{Log\+Probability}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Log\+Probability()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily void Log\+Probability (\begin{DoxyParamCaption}\item[{const arma\+::mat \&}]{observations, }\item[{arma\+::vec \&}]{log\+Probabilities }\end{DoxyParamCaption}) const} Calculate the multivariate Gaussian log probability density function for each data point (column) in the given matrix. \begin{DoxyParams}{Parameters} {\em observations} & Matrix of observations. \\ \hline {\em log\+Probabilities} & Output log probabilities for each observation. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a6db5f5d76cbd055347cecd9ca90eea86}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Mean@{Mean}} \index{Mean@{Mean}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Mean()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily const arma\+::vec\& Mean (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Return the mean. Definition at line 127 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a94becb1cd872c0334328c37f130db253}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Mean@{Mean}} \index{Mean@{Mean}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Mean()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily arma\+::vec\& Mean (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Return a modifiable copy of the mean. Definition at line 130 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_ab72935d592516e77511d0b5e703c0d41}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Probability@{Probability}} \index{Probability@{Probability}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Probability()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily double Probability (\begin{DoxyParamCaption}\item[{const arma\+::vec \&}]{observation }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Return the probability of the given observation. Definition at line 67 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. References Diagonal\+Gaussian\+Distribution\+::\+Log\+Probability(). \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a1e516aca34e9c99caf1431a822d87fc6}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Probability@{Probability}} \index{Probability@{Probability}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Probability()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily void Probability (\begin{DoxyParamCaption}\item[{const arma\+::mat \&}]{x, }\item[{arma\+::vec \&}]{probabilities }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Calculate the multivariate Gaussian probability density function for each data point (column) in the given matrix. \begin{DoxyParams}{Parameters} {\em x} & Matrix of observations. \\ \hline {\em probabilities} & Output probabilities for each input observation. \\ \hline \end{DoxyParams} Definition at line 82 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. References Diagonal\+Gaussian\+Distribution\+::\+Log\+Probability(), Diagonal\+Gaussian\+Distribution\+::\+Random(), and Diagonal\+Gaussian\+Distribution\+::\+Train(). \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a2c6f8d5bb4eacf7de767d2172b320756}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Random@{Random}} \index{Random@{Random}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Random()} {\footnotesize\ttfamily arma\+::vec Random (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const} Return a randomly generated observation according to the probability distribution defined by this object. \begin{DoxyReturn}{Returns} Random observation from this Diagonal Gaussian distribution. \end{DoxyReturn} Referenced by Diagonal\+Gaussian\+Distribution\+::\+Probability(). \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_af0dd9205158ccf7bcfcd8ff81f79c927}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!serialize@{serialize}} \index{serialize@{serialize}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{serialize()} {\footnotesize\ttfamily void serialize (\begin{DoxyParamCaption}\item[{Archive \&}]{ar, }\item[{const unsigned}]{int }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Serialize the distribution. Definition at line 143 of file diagonal\+\_\+gaussian\+\_\+distribution.\+hpp. \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_a269c6f8a40ce41a5f7b6d035aef58238}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Train@{Train}} \index{Train@{Train}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Train()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily void Train (\begin{DoxyParamCaption}\item[{const arma\+::mat \&}]{observations }\end{DoxyParamCaption})} Estimate the Gaussian distribution directly from the given observations. \begin{DoxyParams}{Parameters} {\em observations} & Matrix of observations. \\ \hline \end{DoxyParams} Referenced by Diagonal\+Gaussian\+Distribution\+::\+Probability(). \mbox{\label{classmlpack_1_1distribution_1_1DiagonalGaussianDistribution_ad71152f8853ac60c92a165ed72384125}} \index{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}!Train@{Train}} \index{Train@{Train}!mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution@{mlpack\+::distribution\+::\+Diagonal\+Gaussian\+Distribution}} \subsubsection{Train()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily void Train (\begin{DoxyParamCaption}\item[{const arma\+::mat \&}]{observations, }\item[{const arma\+::vec \&}]{probabilities }\end{DoxyParamCaption})} Estimate the Gaussian distribution from the given observations, taking into account the probability of each observation actually being from this distribution. \begin{DoxyParams}{Parameters} {\em observations} & Matrix of observations. \\ \hline {\em probabilities} & List of probability of the each observation being from this distribution. \\ \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-\/git/src/mlpack/core/dists/\textbf{ diagonal\+\_\+gaussian\+\_\+distribution.\+hpp}\end{DoxyCompactItemize}