PLearn::LogOfGaussianDensityKernel Class Reference

#include <LogOfGaussianDensityKernel.h>

Inheritance diagram for PLearn::LogOfGaussianDensityKernel:

[legend]Collaboration diagram for PLearn::LogOfGaussianDensityKernel:

[legend]List of all members.

Public Member Functions
	LogOfGaussianDensityKernel ()
	LogOfGaussianDensityKernel (real the_sigma)
	PLEARN_DECLARE_OBJECT (LogOfGaussianDensityKernel)
virtual real	evaluate (const Vec &x1, const Vec &x2) const
	returns K(x1,x2)
Static Protected Member Functions
void	declareOptions (OptionList &ol)
	redefine this in subclasses: call declareOption(...) for each option, and then call inherited::declareOptions(options) ( see the declareOption function further down)
Protected Attributes
real	sigma
Private Types
typedef Kernel	inherited

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Detailed Description

computes the log of a GaussianDensityKernel logp = log[ exp(-0.5*norm_2(x1-x2)^2/sigma^2)/(sigma*sqrt(2pi))^n ] = log[ exp(-0.5*norm_2(x1-x2)^2/sigma^2)/exp(log[(sigma*sqrt(2pi))^n]) ] = log[ exp(-0.5*norm_2(x1-x2)^2/sigma^2)/exp(log[(2pi*sigma^2)^(n/2)]) ] = -0.5* [ norm_2(x1-x2)^2/sigma^2 + n*( log(2pi) + log(sigma^2) ) ] where n=x1.length().

Definition at line 60 of file LogOfGaussianDensityKernel.h.

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Member Typedef Documentation

typedef Kernel PLearn::LogOfGaussianDensityKernel::inherited [private]

Reimplemented from PLearn::Kernel. Definition at line 62 of file LogOfGaussianDensityKernel.h.

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Constructor & Destructor Documentation

PLearn::LogOfGaussianDensityKernel::LogOfGaussianDensityKernel (   )  [inline]

Definition at line 68 of file LogOfGaussianDensityKernel.h. References sigma.

PLearn::LogOfGaussianDensityKernel::LogOfGaussianDensityKernel (  real  the_sigma  )  [inline]

Definition at line 70 of file LogOfGaussianDensityKernel.h. References sigma.

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Member Function Documentation

void PLearn::LogOfGaussianDensityKernel::declareOptions (  OptionList &  ol  )  [static, protected]

redefine this in subclasses: call declareOption(...) for each option, and then call inherited::declareOptions(options) ( see the declareOption function further down) ex: static void declareOptions(OptionList& ol) { declareOption(ol, "inputsize", &MyObject::inputsize_, OptionBase::buildoption, "the size of the input\n it must be provided"); declareOption(ol, "weights", &MyObject::weights, OptionBase::learntoption, "the learnt model weights"); inherited::declareOptions(ol); } Reimplemented from PLearn::Kernel. Definition at line 67 of file LogOfGaussianDensityKernel.cc. References PLearn::declareOption(), and PLearn::OptionList.

real PLearn::LogOfGaussianDensityKernel::evaluate (  const Vec &  x1, const Vec &  x2 )  const [virtual]

returns K(x1,x2) Implements PLearn::Kernel. Definition at line 51 of file LogOfGaussianDensityKernel.cc. References PLearn::TVec< T >::length(), PLearn::log(), Pi, PLearn::powdistance(), sigma, and PLearn::Vec.

PLearn::LogOfGaussianDensityKernel::PLEARN_DECLARE_OBJECT (  LogOfGaussianDensityKernel   )

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Member Data Documentation

real PLearn::LogOfGaussianDensityKernel::sigma [protected]

Definition at line 65 of file LogOfGaussianDensityKernel.h. Referenced by evaluate(), and LogOfGaussianDensityKernel().

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

• LogOfGaussianDensityKernel.h
• LogOfGaussianDensityKernel.cc

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