ARLK::BaseClassifier Class Reference

#include <BaseClassifier.h>

Inheritance diagram for ARLK::BaseClassifier:

Public Member Functions
	BaseClassifier ()
	~BaseClassifier ()
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.

Static Public Member Functions
static int **	genConfusionMatrix (double *predictedLabels, double *trueLabels, int num, int labelTypeNum)

Static Protected Member Functions
static bool	CalFeatureVector (SkeData *inputData, int frameIdx, int vecIdx, FEATURE_VEC *pSkdPointOut, double wt)

Protected Attributes
int	dataNum
	Number of the data.
double *	labels
double	actWeight

Constructor & Destructor Documentation

ARLK::BaseClassifier::BaseClassifier

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)

ARLK::BaseClassifier::~BaseClassifier

(

)

Member Function Documentation

bool ARLK::BaseClassifier::CalFeatureVector ( SkeData *  inputData, int  frameIdx, int  vecIdx, FEATURE_VEC *  pSkdPointOut, double  wt  )

staticprotected

Calculate a feature vector for one frame.

Parameters

[in]	inputData	SkeData containing all training data information
[in]	frameIdx	Frame index, counting from 1
[in]	vecIdx	Vector index, counting from 1
[out]	pSkdPointOut	A FEATURE_VEC structure containing the calculated vector
[in]	wt	Weight of the velocity features

Returns

A bool value, true if succeeds

void ARLK::BaseClassifier::CleanData ( )

virtual

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

Reimplemented in ARLK::SVMClassifier, and ARLK::KNNClassifier.

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

inlinevirtual

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 in ARLK::SVMClassifier, and ARLK::KNNClassifier.

int ** ARLK::BaseClassifier::genConfusionMatrix ( double *  predictedLabels, double *  trueLabels, int  num, int  labelTypeNum  )

static

Generate the confusion matrix according to the predicted results Assuming the label numbers can be casted to integers

Parameters

[in]	predictedLabels	A pointer to the buffer containing the predicted labels of the test data
[in]	trueLabels	A pointer to the buffer containing the true labels of the test data
[in]	num	Number of the test data
[in]	labelTypeNum	A pointer to a integer containing the number of label types

Returns

A double pointer to the confusion matrix, should be deleted by the user

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

inlinevirtual

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 in ARLK::SVMClassifier, and ARLK::KNNClassifier.

virtual bool ARLK::BaseClassifier::train ( )

inlinevirtual

Return true if the training process succeeds.

Reimplemented in ARLK::SVMClassifier, and ARLK::KNNClassifier.

Member Data Documentation

double ARLK::BaseClassifier::actWeight

protected

int ARLK::BaseClassifier::dataNum

protected

Number of the data.

double* ARLK::BaseClassifier::labels

protected

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

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