plLearnNdNormal Class Reference

This class permits to learn multi-dimensional Normal (Gaussian) distributions. More...

#include <plLearnNdNormal.h>

Inheritance diagram for plLearnNdNormal:

[legend]Collaboration diagram for plLearnNdNormal:

[legend]List of all members.

Public Member Functions
	plLearnNdNormal (const plVariablesConjunction &vars)
	Constructor using a set of variables.
	plLearnNdNormal (const plVariablesConjunction &vars, const plFloatVector &init_mean, const plFloatMatrix &init_matrix, double init_weight=1.0)
	Constructor using a set of variables, an initial mean, initial covariance, and an initial weight .
	plLearnNdNormal ()
	Void default constructor.
virtual	~plLearnNdNormal ()
	Dectructor.
void	reset ()
	Resets learning.
void	internal_addPoint (const plDataValues &point, double weight=1.0)
	Adds a point {point} with a given weight {weight} and updates the mean and covariances statistics.
void	getMean (plFloatVector &mean) const
	Returns the mean vector in the output parameter {mean}.{mean} is assumed to have the correct size.
plFloatVector	getMean () const
	Returns the mean vector.
void	getCovariance (plFloatMatrix &covariance) const
	Returns the covariance matrix in the output parameter {covariance}.
plFloatMatrix	getCovariance () const
	Returns the covariance matrix.
void	get_params (plValues &params) const
	Returns the {dim+dim^2} parameters of the dim-dimensional Normal distribution.
void	get_actual_min_max (plFloatVector &min, plFloatVector &max) const
	Returns min and max values.
plKernel	get_distribution (const void *parameters=NULL) const
	Returns the normal corresponding to the learnt distribution.

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Detailed Description

This class permits to learn multi-dimensional Normal (Gaussian) distributions.

Definition at line 33 of file plLearnNdNormal.h.

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Member Function Documentation

void plLearnNdNormal::get_params (  plValues &  params  )  const [virtual]

Returns the {dim+dim^2} parameters of the dim-dimensional Normal distribution. The output parameter {params} will contain the {dim} values of the mean vector and the {dim^2} values of the covariance matrix. Implements plNonCndLearnObject.

void plLearnNdNormal::getCovariance (  plFloatMatrix &  covariance  )  const

Returns the covariance matrix in the output parameter {covariance}. {covariance} is assumed to have the correct size.

void plLearnNdNormal::internal_addPoint (  const plDataValues &  point, double  weight = 1.0 )  [virtual]

Adds a point {point} with a given weight {weight} and updates the mean and covariances statistics. This is an internal method, do not use it directly. Use addNewPoint instead. Implements plLearnObject.

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

• plLearnNdNormal.h

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