ARLK::KNNClassifier Class Reference

#include <KNNClassifier.h>

Inheritance diagram for ARLK::KNNClassifier:

Public Member Functions
	KNNClassifier ()
	~KNNClassifier ()
void	SetKNNParameters (int K, double eps, double weight)
	By default K = 10, eps = 0, weight = 3.
virtual bool	FeatureExtraction (SkeData *inputData, const double *dataLabels=NULL, int labelNum=0)
virtual bool	train ()
	Return true if the training process succeeds.
virtual double *	predict (SkeData *inputData, int *pLength)
virtual void	CleanData ()
	Clean all the data except actWeight and set datanum to 0.
Public Member Functions inherited from ARLK::BaseClassifier
	BaseClassifier ()
	~BaseClassifier ()

Additional Inherited Members
Static Public Member Functions inherited from ARLK::BaseClassifier
static int **	genConfusionMatrix (double *predictedLabels, double *trueLabels, int num, int labelTypeNum)
Static Protected Member Functions inherited from ARLK::BaseClassifier
static bool	CalFeatureVector (SkeData *inputData, int frameIdx, int vecIdx, FEATURE_VEC *pSkdPointOut, double wt)
Protected Attributes inherited from ARLK::BaseClassifier
int	dataNum
	Number of the data.
double *	labels
double	actWeight

Constructor & Destructor Documentation

ARLK::KNNClassifier::KNNClassifier

(

)

ARLK::KNNClassifier::~KNNClassifier

(

)

Member Function Documentation

void ARLK::KNNClassifier::CleanData ( )

virtual

Clean all the data except actWeight and set datanum to 0.

Reimplemented from ARLK::BaseClassifier.

bool ARLK::KNNClassifier::FeatureExtraction ( SkeData *  inputData, const double *  dataLabels = NULL, int  labelNum = 0  )

virtual

Extract features from SkeData

Parameters

[in]	inputData	SkeData containing all training data information
[in]	dataLabels	An array containing the data labels for each training data
[in]	labelNum	Number of labels/training data

Returns

True if succeeds

Reimplemented from ARLK::BaseClassifier.

double * ARLK::KNNClassifier::predict ( SkeData *  inputData, int *  pLength  )

virtual

Classify the data in inputData, store the results in the buffer pointed by labelBuf

Parameters

[in]	inputData	SkeData containing all test data information
[out]	pLength	Pointer to the integer indicating the length of the buffer of the predicted labels

Returns

A pointer to the buffer containing the predicted double labels, should be deleted by the user

Reimplemented from ARLK::BaseClassifier.

void ARLK::KNNClassifier::SetKNNParameters	(	int	K,
		double	eps,
		double	weight
	)

By default K = 10, eps = 0, weight = 3.

bool ARLK::KNNClassifier::train ( )

virtual

Return true if the training process succeeds.

Reimplemented from ARLK::BaseClassifier.

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

• include/ARLK/KNNClassifier.h
• src/ARLK/KNNClassifier.cpp