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fl::Kohonen Class Reference

#include <cluster.h>

Inheritance diagram for fl::Kohonen:

List of all members.

Public Methods
	Kohonen (int width, float sigma=1.0, float learningRate=0.1, float decayRate=0.5)
	Kohonen (std::istream &stream)
virtual void	run (const std::vector< Vector< float > > &data)
	Peform clustering on collection of points.
virtual int	classify (const Vector< float > &point)
	Determine the single best class of given point.
virtual Vector< float >	distribution (const Vector< float > &point)
	Return a probability distribution over the classes. Row number in the returned Vector corresponds to class number.
virtual int	classCount ()
	Returns the number of classes.
virtual Vector< float >	representative (int group)
	Return a representative member of group. "group" has same semantics as return value of classify (); we just can't use the word "class" because it is a keyword in C++. :).
virtual void	read (std::istream &stream)
virtual void	write (std::ostream &stream, bool withName=false)
Public Attributes
std::vector< ClusterCosine >	map
int	width
	Number of discrete positions in one dimension.
float	sigma
	Of Gaussian that determines neighborhood to be updated.
float	learningRate
	How much to scale feature vector during update.
float	decayRate
	How much to scale learningRate after each iteration.

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Constructor & Destructor Documentation

Kohonen::Kohonen (  int    width, float    sigma = 1.0, float    learningRate = 0.1, float    decayRate = 0.5 )

Kohonen::Kohonen (  std::istream &    stream )

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Member Function Documentation

int Kohonen::classCount (    )  [virtual]

Returns the number of classes. Implements fl::ClusterMethod.

int Kohonen::classify (  const Vector< float > &    point )  [virtual]

Determine the single best class of given point. Implements fl::ClusterMethod.

Vector< float > Kohonen::distribution (  const Vector< float > &    point )  [virtual]

Return a probability distribution over the classes. Row number in the returned Vector corresponds to class number. Implements fl::ClusterMethod.

void Kohonen::read (  std::istream &    stream )  [virtual]

Reimplemented from fl::ClusterMethod.

Vector< float > Kohonen::representative (  int    group )  [virtual]

Return a representative member of group. "group" has same semantics as return value of classify (); we just can't use the word "class" because it is a keyword in C++. :). Implements fl::ClusterMethod.

void Kohonen::run (  const std::vector< Vector< float > > &    data )  [virtual]

Peform clustering on collection of points. Implements fl::ClusterMethod.

void Kohonen::write (  std::ostream &    stream, bool    withName = false )  [virtual]

Reimplemented from fl::ClusterMethod.

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Member Data Documentation

float fl::Kohonen::decayRate

How much to scale learningRate after each iteration.

float fl::Kohonen::learningRate

How much to scale feature vector during update.

std::vector<ClusterCosine> fl::Kohonen::map

float fl::Kohonen::sigma

Of Gaussian that determines neighborhood to be updated.

int fl::Kohonen::width

Number of discrete positions in one dimension.

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

• cluster.h
• Kohonen.cc

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