CKNN Class Reference

Inheritance diagram for CKNN:

[legend]

List of all members.

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Detailed Description

class KNN

Definition at line 25 of file KNN.h.

Public Member Functions
	CKNN ()
	CKNN (INT k, CDistance *d, CLabels *trainlab)
virtual	~CKNN ()
virtual EClassifierType	get_classifier_type ()
virtual bool	train ()
virtual CLabels *	classify (CLabels *output=NULL)
virtual DREAL	classify_example (INT vec_idx)
	get output for example "vec_idx"
virtual bool	load (FILE *srcfile)
virtual bool	save (FILE *dstfile)
void	set_k (DREAL p_k)
DREAL	get_k ()
void	set_distance (CDistance *d)
CDistance *	get_distance ()
virtual void	set_labels (CLabels *lab)
virtual CLabels *	get_labels ()
virtual DREAL	get_label (INT i)
void	set_max_train_time (DREAL t)
DREAL	get_max_train_time ()
Static Public Attributes
static CParallel	parallel
static CIO	io
static CVersion	version
Protected Attributes
DREAL	k
	the k parameter in KNN
int	num_classes
	number of classes (i.e. number of values labels can take)
int	min_label
	smallest label, i.e. -1
int	num_train_labels
	number of train examples
INT *	train_labels
	the actual trainlabels
CDistance *	distance
DREAL	max_train_time
CLabels *	labels

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Constructor & Destructor Documentation

CKNN::CKNN

(

)

default constructor

Definition at line 17 of file KNN.cpp.

CKNN::CKNN	(	INT	k,
		CDistance *	d,
		CLabels *	trainlab
	)

constructor

Parameters:

	k	k
	d	distance
	trainlab	labels for training

Definition at line 22 of file KNN.cpp.

CKNN::~CKNN

(

)

[virtual]

Definition at line 31 of file KNN.cpp.

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Member Function Documentation

virtual EClassifierType CKNN::get_classifier_type

(

)

[virtual]

get classifier type

Returns:

classifier type KNN

Reimplemented from CClassifier.

Definition at line 44 of file KNN.h.

bool CKNN::train

(

)

[virtual]

train classifier

Returns:

if training was successful

Reimplemented from CClassifier.

Definition at line 36 of file KNN.cpp.

CLabels * CKNN::classify

(

CLabels *

output = NULL

)

[virtual]

classify all examples

Parameters:

output

resulting labels

Returns:

resulting labels

histogram of classes and returned output

Reimplemented from CClassifier.

Definition at line 64 of file KNN.cpp.

virtual DREAL CKNN::classify_example

(

INT

vec_idx

)

[virtual]

get output for example "vec_idx"

Reimplemented from CClassifier.

Definition at line 61 of file KNN.h.

bool CKNN::load

(

FILE *

srcfile

)

[virtual]

load from file

Parameters:

srcfile

file to load from

Returns:

if loading was successful

Reimplemented from CClassifier.

Definition at line 137 of file KNN.cpp.

bool CKNN::save

(

FILE *

dstfile

)

[virtual]

save to file

Parameters:

dstfile

file to save to

Returns:

if saving was successful

Reimplemented from CClassifier.

Definition at line 142 of file KNN.cpp.

void CKNN::set_k

(

DREAL

p_k

)

set k

Parameters:

p_k

new k

Definition at line 85 of file KNN.h.

DREAL CKNN::get_k

(

)

get k

Returns:

k

Definition at line 95 of file KNN.h.

void CDistanceMachine::set_distance

(

CDistance *

d

)

[inherited]

set distance

Parameters:

d

distance to set

Definition at line 34 of file DistanceMachine.h.

CDistance* CDistanceMachine::get_distance

(

)

[inherited]

get distance

Returns:

distance

Definition at line 45 of file DistanceMachine.h.

virtual void CClassifier::set_labels

(

CLabels *

lab

)

[virtual, inherited]

set labels

Parameters:

lab

labels

Definition at line 71 of file Classifier.h.

virtual CLabels* CClassifier::get_labels

(

)

[virtual, inherited]

get labels

Returns:

labels

Definition at line 82 of file Classifier.h.

virtual DREAL CClassifier::get_label

(

INT

i

)

[virtual, inherited]

get one specific label

Parameters:

i

index of label to get

Returns:

value of label at index i

Definition at line 89 of file Classifier.h.

void CClassifier::set_max_train_time

(

DREAL

t

)

[inherited]

set maximum training time

Parameters:

t

maximimum training time

Definition at line 95 of file Classifier.h.

DREAL CClassifier::get_max_train_time

(

)

[inherited]

get maximum training time

Returns:

maximum training time

Definition at line 101 of file Classifier.h.

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Member Data Documentation

DREAL CKNN::k [protected]

the k parameter in KNN

Definition at line 102 of file KNN.h.

int CKNN::num_classes [protected]

number of classes (i.e. number of values labels can take)

Definition at line 105 of file KNN.h.

int CKNN::min_label [protected]

smallest label, i.e. -1

Definition at line 108 of file KNN.h.

int CKNN::num_train_labels [protected]

number of train examples

Definition at line 111 of file KNN.h.

INT* CKNN::train_labels [protected]

the actual trainlabels

Definition at line 114 of file KNN.h.

CDistance* CDistanceMachine::distance [protected, inherited]

the distance

Definition at line 49 of file DistanceMachine.h.

DREAL CClassifier::max_train_time [protected, inherited]

maximum training time

Definition at line 111 of file Classifier.h.

CLabels* CClassifier::labels [protected, inherited]

labels

Definition at line 114 of file Classifier.h.

CParallel CSGObject::parallel [static, inherited]

Definition at line 105 of file SGObject.h.

CIO CSGObject::io [static, inherited]

Definition at line 106 of file SGObject.h.

CVersion CSGObject::version [static, inherited]

Definition at line 107 of file SGObject.h.

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

• KNN.h
• KNN.cpp