mlpack::ann::NormalDistribution< DataType > Class Template Reference

Implementation of the Normal Distribution function. More...

#include <normal_distribution.hpp>

Public Member Functions
	NormalDistribution ()
	Default constructor, which creates a Normal distribution with zero dimension.
	NormalDistribution (const DataType &mean, const DataType &sigma)
	Create a Normal distribution with the given mean and sigma. More...
DataType	Probability (const DataType &observation) const
	Return the probabilities of the given matrix of observations. More...
DataType	LogProbability (const DataType &observation) const
	Return the log probabilities of the given matrix of observations. More...
void	ProbBackward (const DataType &observation, DataType &dmu, DataType &dsigma) const
	Stores the gradient of the probabilities of the observations with respect to mean and standard deviation. More...
void	Probability (const DataType &x, DataType &probabilities) const
	Calculates the normal probability density function for each data point (column) in the given matrix. More...
void	LogProbability (const DataType &x, DataType &probabilities) const
	Calculates the log of normal probability density function for each data point (column) in the given matrix. More...
DataType	Sample () const
	Return a randomly generated observation according to the probability distribution defined by this object. More...
const DataType &	Mean () const
	Get the mean.
DataType &	Mean ()
	Modify the mean.
const DataType &	StandardDeviation () const
	Get the standard deviation.
DataType &	StandardDeviation ()
	Modify the standard deviation.
size_t	Dimensionality () const
	Return the dimensionality of this distribution.
template<typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the distribution.

Detailed Description

template<typename DataType = arma::mat>
class mlpack::ann::NormalDistribution< DataType >

Implementation of the Normal Distribution function.

Normal distribution is a function which accepts a mean and a standard deviation term and creates a probability distribution out of it.

Template Parameters

DataType

Type of the input data. (arma::colvec, arma::mat, arma::sp_mat or arma::cube).

Constructor & Destructor Documentation

NormalDistribution()

template<typename DataType >

mlpack::ann::NormalDistribution< DataType >::NormalDistribution	(	const DataType &	mean,
		const DataType &	sigma
	)

Create a Normal distribution with the given mean and sigma.

Parameters

mean	The mean of the normal distribution.
sigma	The standard deviation of the normal distribution.

Member Function Documentation

LogProbability() [1/2]

template<typename DataType >

DataType mlpack::ann::NormalDistribution< DataType >::LogProbability

(

const DataType &

observation

)

const

Return the log probabilities of the given matrix of observations.

Parameters

observation

The observation matrix.

LogProbability() [2/2]

template<typename DataType = arma::mat>

void mlpack::ann::NormalDistribution< DataType >::LogProbability ( const DataType &  x, DataType &  probabilities  ) const

inline

Calculates the log of normal probability density function for each data point (column) in the given matrix.

Parameters

x	The observation matrix.
probabilities	Output log probabilities for each input observation.

Probability() [1/2]

template<typename DataType = arma::mat>

DataType mlpack::ann::NormalDistribution< DataType >::Probability ( const DataType &  observation ) const

inline

Return the probabilities of the given matrix of observations.

Parameters

observation

The observation matrix.

Probability() [2/2]

template<typename DataType = arma::mat>

void mlpack::ann::NormalDistribution< DataType >::Probability ( const DataType &  x, DataType &  probabilities  ) const

inline

Calculates the normal probability density function for each data point (column) in the given matrix.

Parameters

x	The observation matrix.
probabilities	Output probabilities for each input observation.

ProbBackward()

template<typename DataType >

void mlpack::ann::NormalDistribution< DataType >::ProbBackward	(	const DataType &	observation,
		DataType &	dmu,
		DataType &	dsigma
	)		const

Stores the gradient of the probabilities of the observations with respect to mean and standard deviation.

Parameters

observation	The observation matrix.
dmu	The gradient with respect to mean.
dsigma	The gradient with respect to the standard deviation.

Sample()

template<typename DataType >

DataType mlpack::ann::NormalDistribution< DataType >::Sample

(

)

const

Return a randomly generated observation according to the probability distribution defined by this object.

Returns

Random observation from this Normal distribution.

---

The documentation for this class was generated from the following files:

• src/mlpack/methods/ann/dists/normal_distribution.hpp
• src/mlpack/methods/ann/dists/normal_distribution_impl.hpp