A Support Vector Machine Binary Classifier. More...

#include <clsfy_rbf_svm.h>

Inheritance diagram for clsfy_rbf_svm:

Public Member Functions
	clsfy_rbf_svm ()
	Dflt constructor.
virtual	~clsfy_rbf_svm ()
	Destructor.
virtual unsigned	classify (const vnl_vector< double > &input) const
	Classify the input vector.
virtual void	class_probabilities (vcl_vector< double > &outputs, const vnl_vector< double > &input) const
	Return the probability the input being in each class.
virtual double	log_l (const vnl_vector< double > &input) const
	Log likelihood of being in class (binary classifiers only).
virtual void	set (const vcl_vector< vnl_vector< double > > &supportVectors, const vcl_vector< double > &lagrangianAlphas, const vcl_vector< unsigned > &labels, double RBFWidth, double bias)
	Set the internal values defining the classifier.
double	rbf_width () const
	The 1st standard deviation width of the RBF kernel.
unsigned	n_support_vectors () const
	The number of support vectors.
double	kernel (const vnl_vector< double > &v1, const vnl_vector< double > &v2) const
	The kernel function.
double	bias () const
	The SVM function bias.
const vcl_vector< double > &	lagrangians () const
	The Lagrange multipliers.
const vcl_vector< vnl_vector < double > > &	support_vectors () const
	The support vectors.
virtual unsigned	n_classes () const
	The number of possible output classes.
virtual unsigned	n_dims () const
	The dimensionality of input vectors.
short	version_no () const
	Return the class's IO 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.
Protected Member Functions
void	calculate_targets ()
	Set the private target member values to the correct value.
double	localEuclideanDistanceSq (const vnl_vector< double > &a, const vnl_vector< double > &b) const
	Calculate the contribution of a single support vector to the classifier;.
Protected Attributes
double	upper_target_
	the starting upper bound.
double	lower_target_
	the starting lower bound.
vcl_vector< vnl_vector< double > >	supports_
	The support vectors.
vcl_vector< double >	lagrangians_
	The Lagrangian multipliers.
double	bias_
	The offset bias.
double	gamma_

Detailed Description

A Support Vector Machine Binary Classifier.

Definition at line 21 of file clsfy_rbf_svm.h.

Constructor & Destructor Documentation

clsfy_rbf_svm::clsfy_rbf_svm ( )

Dflt constructor.

Definition at line 20 of file clsfy_rbf_svm.cxx.

clsfy_rbf_svm::~clsfy_rbf_svm ( ) [virtual]

Destructor.

Definition at line 26 of file clsfy_rbf_svm.cxx.

Member Function Documentation

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

Load class from binary file stream.

Implements clsfy_classifier_base.

Definition at line 192 of file clsfy_rbf_svm.cxx.

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

Save class to binary file stream.

Implements clsfy_classifier_base.

Definition at line 181 of file clsfy_rbf_svm.cxx.

double clsfy_rbf_svm::bias ( ) const [inline]

The SVM function bias.

Definition at line 91 of file clsfy_rbf_svm.h.

void clsfy_rbf_svm::calculate_targets ( ) [protected]

Set the private target member values to the correct value.

Definition at line 103 of file clsfy_rbf_svm.cxx.

void clsfy_rbf_svm::class_probabilities	(	vcl_vector< double > &	outputs,
		const vnl_vector< double > &	input
	)		const `[virtual]`

Return the probability the input being in each class.

output(i) i<<nClasses, contains the probability that the input is in class i; This are not strict probability values, since SVMs do not give Bayesian outputs. However their properties fit the requirements of a probability.

Implements clsfy_classifier_base.

Definition at line 88 of file clsfy_rbf_svm.cxx.

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

Classify the input vector.

returns 0 to indicate out of (or negative) class and one to indicate in class (or positive.)

Returns 0 to indicate out of (or negative) class and one to indicate in class (or positive.)

Reimplemented from clsfy_classifier_base.

Definition at line 44 of file clsfy_rbf_svm.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_svm::clone ( ) const [virtual]

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

Implements clsfy_classifier_base.

Definition at line 164 of file clsfy_rbf_svm.cxx.

vcl_string clsfy_rbf_svm::is_a ( ) const [virtual]

Name of the class.

Reimplemented from clsfy_classifier_base.

Definition at line 143 of file clsfy_rbf_svm.cxx.

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

Name of the class.

Reimplemented from clsfy_classifier_base.

Definition at line 150 of file clsfy_rbf_svm.cxx.

double clsfy_rbf_svm::kernel	(	const vnl_vector< double > &	v1,
		const vnl_vector< double > &	v2
	)		const

The kernel function.

Uses the SVM's current value of RBFWidth.

Definition at line 33 of file clsfy_rbf_svm.cxx.

const vcl_vector<double>& clsfy_rbf_svm::lagrangians ( ) const [inline]

The Lagrange multipliers.

The values corresponding to negative training vectors are pre-multiplied by -1. The array ordering corresponds to supportVectors()

Definition at line 96 of file clsfy_rbf_svm.h.

double clsfy_rbf_svm::localEuclideanDistanceSq	(	const vnl_vector< double > &	a,
		const vnl_vector< double > &	b
	)		const `[inline, protected]`

Calculate the contribution of a single support vector to the classifier;.

This local version is used so that the number of calls can be tested.

Definition at line 136 of file clsfy_rbf_svm.h.

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

Log likelihood of being in class (binary classifiers only).

class probability = vcl_exp(logL) / (1+vcl_exp(logL)

class probability = vcl_exp(logL) / (1+vcl_exp(logL)) This is not a strict log likelihood value, since SVMs do not give Bayesian outputs. However its properties fit the requirements of a log likelihood value.

Implements clsfy_classifier_base.

Definition at line 72 of file clsfy_rbf_svm.cxx.

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

The number of possible output classes.

Implements clsfy_classifier_base.

Definition at line 104 of file clsfy_rbf_svm.h.

virtual unsigned clsfy_rbf_svm::n_dims ( ) const [inline, virtual]

The dimensionality of input vectors.

Implements clsfy_classifier_base.

Definition at line 107 of file clsfy_rbf_svm.h.

unsigned clsfy_rbf_svm::n_support_vectors ( ) const [inline]

The number of support vectors.

Definition at line 84 of file clsfy_rbf_svm.h.

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

Print class to os.

Implements clsfy_classifier_base.

Definition at line 171 of file clsfy_rbf_svm.cxx.

double clsfy_rbf_svm::rbf_width ( ) const [inline]

The 1st standard deviation width of the RBF kernel.

Really this could be better named as the RBF radius.

Definition at line 81 of file clsfy_rbf_svm.h.

void clsfy_rbf_svm::set	(	const vcl_vector< vnl_vector< double > > &	supportVectors,
		const vcl_vector< double > &	lagrangianAlphas,
		const vcl_vector< unsigned > &	labels,
		double	RBFWidth,
		double	bias
	)		`[virtual]`

Set the internal values defining the classifier.

Parameters:

supportVectors
lagrangianAlphas
labels	These should be 0 or 1.
RBFWidth
bias

Definition at line 120 of file clsfy_rbf_svm.cxx.

const vcl_vector<vnl_vector<double> >& clsfy_rbf_svm::support_vectors ( ) const [inline]

The support vectors.

The array ordering corresponds to lagrangians()

Definition at line 100 of file clsfy_rbf_svm.h.

short clsfy_rbf_svm::version_no ( ) const

Return the class's IO version number.

Definition at line 157 of file clsfy_rbf_svm.cxx.

Member Data Documentation

double clsfy_rbf_svm::bias_ [protected]

The offset bias.

Definition at line 39 of file clsfy_rbf_svm.h.

double clsfy_rbf_svm::gamma_ [protected]

-1/(2 * sigma*sigma), where sigma = RBF kernel width.

Definition at line 42 of file clsfy_rbf_svm.h.

vcl_vector<double> clsfy_rbf_svm::lagrangians_ [protected]

The Lagrangian multipliers.

The values have been pre-multiplied by the +/-1.0 depending on the support target.

Definition at line 36 of file clsfy_rbf_svm.h.

double clsfy_rbf_svm::lower_target_ [protected]

the starting lower bound.

If the function sum falls below this value, the decision will definitely be 0.

Definition at line 29 of file clsfy_rbf_svm.h.

vcl_vector<vnl_vector<double> > clsfy_rbf_svm::supports_ [protected]

The support vectors.

Definition at line 32 of file clsfy_rbf_svm.h.

double clsfy_rbf_svm::upper_target_ [protected]

the starting upper bound.

If the function sum exceeds this value, the decision will definitely be 1.

Definition at line 26 of file clsfy_rbf_svm.h.

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

contrib/mul/clsfy/clsfy_rbf_svm.h
contrib/mul/clsfy/clsfy_rbf_svm.cxx

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation