clsfy_rbf_parzen Class Reference

#include <clsfy_rbf_parzen.h>

Inheritance diagram for clsfy_rbf_parzen:

[legend]List of all members.

Detailed Description

A Parzen binary classifier using an RBF Window.

A given vector, x0, is classified, by placing a window defined by w = exp(-1/(2*sigma^p) * |x-x0|^p), and finding the majority prediction of the nearby training vectors, each weighted by the window function.

Definition at line 21 of file clsfy_rbf_parzen.h.

Public Member Functions

clsfy_rbf_parzen ()

Construct a Parzen classifier.

virtual unsigned classify (const vnl_vector< double > &input) const

Return the classification of the given probe vector.

virtual void class_probabilities (vcl_vector< double > &outputs, const vnl_vector< double > &input) const

Provides a probability-like value that the input being in each class.

double weightings (const vnl_vector< double > &input) const

Return the number of proximate training vectors, weighted by the windowing function.

virtual double log_l (const vnl_vector< double > &input) const

This value has properties of a Log likelihood of being in class (binary classifiers only).

void set (const vcl_vector< vnl_vector< double > > &inputs, const vcl_vector< unsigned > &outputs)

Set the training data.

double rbf_width () const

The 1st standard deviation width of the RBF window.

void set_rbf_width (double sigma)

Set the 1st standard deviation width of the RBF window.

double power () const

The value p in the window function $exp(-1/(2*sigma^p) * |x-y|^p)$.

void set_power (double p)

The value p in the window function $exp(-1/(2*sigma^p) * |x-y|^p)$.

const vcl_vector< vnl_vector<
double > > & training_vectors () const

Return a reference to the training vectors.

const vcl_vector< unsigned > & training_classes () const

Return a reference to the training classes.

virtual unsigned n_classes () const

The number of possible output classes.

virtual unsigned n_dims () const

The dimensionality of input vectors.

virtual short version_no () const

Storage version number.

virtual vcl_string is_a () const

Name of the class.

virtual bool is_class (vcl_string const &s) const

Name of the class.

virtual clsfy_classifier_base * clone () const

Create a copy on the heap and return base class pointer.

virtual void print_summary (vcl_ostream &os) const

Print class to os.

virtual void b_write (vsl_b_ostream &bfs) const

Save class to binary file stream.

virtual void b_read (vsl_b_istream &bfs)

Load class from binary file stream.

virtual void classify_many (vcl_vector< unsigned > &outputs, mbl_data_wrapper< vnl_vector< double > > &inputs) const

Classify many input vectors.

Private Attributes

double gamma_

Workspace value which is cached for speed.

double width_

Width of the rbf window function.

double power_

The power, p, in the window function. Default value is 2.0.

vcl_vector< vnl_vector< double > > trainInputs_

The set of training input values. Size should equal number of outputs.

vcl_vector< unsigned > trainOutputs_

The set of training output values. Size should equal number of inputs.

Constructor & Destructor Documentation

clsfy_rbf_parzen::clsfy_rbf_parzen ( ) [inline]

Construct a Parzen classifier.

Definition at line 45 of file clsfy_rbf_parzen.h.

Member Function Documentation

void clsfy_rbf_parzen::b_read ( vsl_b_istream & bfs ) [virtual]

Load class from binary file stream.

Implements clsfy_classifier_base.
Definition at line 205 of file clsfy_rbf_parzen.cxx.

void clsfy_rbf_parzen::b_write ( vsl_b_ostream & bfs ) const [virtual]

Save class to binary file stream.

Implements clsfy_classifier_base.
Definition at line 194 of file clsfy_rbf_parzen.cxx.

void clsfy_rbf_parzen::class_probabilities ( vcl_vector< double > & outputs,

const vnl_vector< double > & input

) const [virtual]

Provides a probability-like value that the input being in each class.
output(i) i<nClasses, contains the probability that the input is in class i
Implements clsfy_classifier_base.
Definition at line 60 of file clsfy_rbf_parzen.cxx.

unsigned clsfy_rbf_parzen::classify ( const vnl_vector< double > & input ) const [virtual]

Return the classification of the given probe vector.

Reimplemented from clsfy_classifier_base.
Definition at line 18 of file clsfy_rbf_parzen.cxx.

void clsfy_classifier_base::classify_many ( vcl_vector< unsigned > & outputs,

mbl_data_wrapper< vnl_vector< double > > & inputs

) const [virtual, inherited]

Classify many input vectors.

Definition at line 55 of file clsfy_classifier_base.cxx.

clsfy_classifier_base * clsfy_rbf_parzen::clone ( ) const [virtual]

Create a copy on the heap and return base class pointer.

Implements clsfy_classifier_base.
Definition at line 179 of file clsfy_rbf_parzen.cxx.

vcl_string clsfy_rbf_parzen::is_a ( ) const [virtual]

Name of the class.

Reimplemented from clsfy_classifier_base.
Definition at line 158 of file clsfy_rbf_parzen.cxx.

bool clsfy_rbf_parzen::is_class ( vcl_string const & s ) const [virtual]

Name of the class.

Reimplemented from clsfy_classifier_base.
Definition at line 165 of file clsfy_rbf_parzen.cxx.

double clsfy_rbf_parzen::log_l ( const vnl_vector< double > & input ) const [virtual]

This value has properties of a Log likelihood of being in class (binary classifiers only).
class probability = exp(logL) / (1+exp(logL))
Implements clsfy_classifier_base.
Definition at line 124 of file clsfy_rbf_parzen.cxx.

virtual unsigned clsfy_rbf_parzen::n_classes ( ) const [inline, virtual]

The number of possible output classes.

Implements clsfy_classifier_base.
Definition at line 96 of file clsfy_rbf_parzen.h.

unsigned clsfy_rbf_parzen::n_dims ( ) const [virtual]

The dimensionality of input vectors.

Implements clsfy_classifier_base.
Definition at line 113 of file clsfy_rbf_parzen.cxx.

double clsfy_rbf_parzen::power ( ) const [inline]

The value p in the window function $exp(-1/(2*sigma^p) * |x-y|^p)$.
The value p affects the kurtosis, or peakyness of the window. Towards 0 gives a more peaked central spike, and longer tail. Toward +inf gives a broader peak, and shorter tail. The default value is 2, giving a Gaussian distribution.
Definition at line 76 of file clsfy_rbf_parzen.h.

void clsfy_rbf_parzen::print_summary ( vcl_ostream & os ) const [virtual]

Print class to os.

Implements clsfy_classifier_base.
Definition at line 186 of file clsfy_rbf_parzen.cxx.

double clsfy_rbf_parzen::rbf_width ( ) const [inline]

The 1st standard deviation width of the RBF window.
The default value is 1.
Definition at line 66 of file clsfy_rbf_parzen.h.

void clsfy_rbf_parzen::set ( const vcl_vector< vnl_vector< double > > & inputs,

const vcl_vector< unsigned > & outputs

)

Set the training data.

Definition at line 48 of file clsfy_rbf_parzen.cxx.

void clsfy_rbf_parzen::set_power ( double p )

The value p in the window function $exp(-1/(2*sigma^p) * |x-y|^p)$.
The value p affects the kurtosis, or peakyness of the window. Towards 0 gives a more peaked central spike, and longer tail. Toward +inf gives a broader peak, and shorter tail. The default value is 2, giving a Gaussian distribution.
Definition at line 149 of file clsfy_rbf_parzen.cxx.

void clsfy_rbf_parzen::set_rbf_width ( double sigma )

Set the 1st standard deviation width of the RBF window.
The default value in the constructor is 1.
Definition at line 135 of file clsfy_rbf_parzen.cxx.

const vcl_vector<unsigned >& clsfy_rbf_parzen::training_classes ( ) const [inline]

Return a reference to the training classes.
Vectors are ordered similarly to training_vectors()
Definition at line 92 of file clsfy_rbf_parzen.h.

const vcl_vector<vnl_vector<double> >& clsfy_rbf_parzen::training_vectors ( ) const [inline]

Return a reference to the training vectors.
Vectors are ordered similarly to training_classes()
Definition at line 87 of file clsfy_rbf_parzen.h.

short clsfy_rbf_parzen::version_no ( ) const [virtual]

Storage version number.

Definition at line 172 of file clsfy_rbf_parzen.cxx.

double clsfy_rbf_parzen::weightings ( const vnl_vector< double > & input ) const

Return the number of proximate training vectors, weighted by the windowing function.

Definition at line 92 of file clsfy_rbf_parzen.cxx.

Member Data Documentation

double clsfy_rbf_parzen::gamma_ [private]

Workspace value which is cached for speed.
Inversely proportional to width of the RBF window function. Default value is -0.5.
width_ = 1/sqrt(-2*gamma_)
Definition at line 27 of file clsfy_rbf_parzen.h.

double clsfy_rbf_parzen::power_ [private]

The power, p, in the window function. Default value is 2.0.

Definition at line 35 of file clsfy_rbf_parzen.h.

vcl_vector<vnl_vector<double> > clsfy_rbf_parzen::trainInputs_ [private]

The set of training input values. Size should equal number of outputs.

Definition at line 38 of file clsfy_rbf_parzen.h.

vcl_vector<unsigned> clsfy_rbf_parzen::trainOutputs_ [private]

The set of training output values. Size should equal number of inputs.

Definition at line 41 of file clsfy_rbf_parzen.h.

double clsfy_rbf_parzen::width_ [private]

Width of the rbf window function.
Default value is 1.0. width_ = 1/sqrt(-2*gamma_)
Definition at line 32 of file clsfy_rbf_parzen.h.

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

contrib/mul/clsfy/clsfy_rbf_parzen.h
contrib/mul/clsfy/clsfy_rbf_parzen.cxx

Generated on Thu Jan 10 14:43:48 2008 for contrib/mul/clsfy by

1.4.4


Public Member Functions
	clsfy_rbf_parzen ()
	Construct a Parzen classifier.
virtual unsigned	classify (const vnl_vector< double > &input) const
	Return the classification of the given probe vector.
virtual void	class_probabilities (vcl_vector< double > &outputs, const vnl_vector< double > &input) const
	Provides a probability-like value that the input being in each class.
double	weightings (const vnl_vector< double > &input) const
	Return the number of proximate training vectors, weighted by the windowing function.
virtual double	log_l (const vnl_vector< double > &input) const
	This value has properties of a Log likelihood of being in class (binary classifiers only).
void	set (const vcl_vector< vnl_vector< double > > &inputs, const vcl_vector< unsigned > &outputs)
	Set the training data.
double	rbf_width () const
	The 1st standard deviation width of the RBF window.
void	set_rbf_width (double sigma)
	Set the 1st standard deviation width of the RBF window.
double	power () const
	The value p in the window function $exp(-1/(2sigma^p) \|x-y\|^p)$.
void	set_power (double p)
	The value p in the window function $exp(-1/(2sigma^p) \|x-y\|^p)$.
const vcl_vector< vnl_vector< double > > &	training_vectors () const
	Return a reference to the training vectors.
const vcl_vector< unsigned > &	training_classes () const
	Return a reference to the training classes.
virtual unsigned	n_classes () const
	The number of possible output classes.
virtual unsigned	n_dims () const
	The dimensionality of input vectors.
virtual short	version_no () const
	Storage version number.
virtual vcl_string	is_a () const
	Name of the class.
virtual bool	is_class (vcl_string const &s) const
	Name of the class.
virtual clsfy_classifier_base *	clone () const
	Create a copy on the heap and return base class pointer.
virtual void	print_summary (vcl_ostream &os) const
	Print class to os.
virtual void	b_write (vsl_b_ostream &bfs) const
	Save class to binary file stream.
virtual void	b_read (vsl_b_istream &bfs)
	Load class from binary file stream.
virtual void	classify_many (vcl_vector< unsigned > &outputs, mbl_data_wrapper< vnl_vector< double > > &inputs) const
	Classify many input vectors.
Private Attributes
double	gamma_
	Workspace value which is cached for speed.
double	width_
	Width of the rbf window function.
double	power_
	The power, p, in the window function. Default value is 2.0.
vcl_vector< vnl_vector< double > >	trainInputs_
	The set of training input values. Size should equal number of outputs.
vcl_vector< unsigned >	trainOutputs_
	The set of training output values. Size should equal number of inputs.