GestureRecognitionToolkit
Version: 1.0 Revision: 04-03-15
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
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MinDistModel.h
Go to the documentation of this file.
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#ifndef GRT_MINDISTMODEL_HEADER
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#define GRT_MINDISTMODEL_HEADER
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#include "../../Util/GRTCommon.h"
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#include "../../ClusteringModules/KMeans/KMeans.h"
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namespace
GRT
{
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class
MinDistModel
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{
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public
:
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MinDistModel
();
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MinDistModel
(
const
MinDistModel
&rhs);
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~MinDistModel
(
void
);
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MinDistModel
&
operator=
(
const
MinDistModel
&rhs);
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bool
train(UINT classLabel,
MatrixDouble
&trainingData,UINT numClusters,
double
minChange,UINT maxNumEpochs);
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double
predict(
const
VectorDouble &observation);
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void
recomputeThresholdValue();
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UINT getClassLabel()
const
;
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UINT getNumFeatures()
const
;
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UINT getNumClusters()
const
;
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UINT getDistanceMode()
const
;
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double
getRejectionThreshold()
const
;
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double
getGamma()
const
;
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double
getTrainingMu()
const
;
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double
getTrainingSigma()
const
;
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MatrixDouble
getClusters()
const
;
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bool
setClassLabel(UINT classLabel);
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bool
setClusters(
MatrixDouble
&clusters);
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bool
setGamma(
double
gamma);
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bool
setRejectionThreshold(
double
rejectionThreshold);
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bool
setTrainingSigma(
double
trainingSigma);
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bool
setTrainingMu(
double
trainingMu);
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private
:
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double
SQR(
double
x){
return
x*x; }
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UINT classLabel;
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UINT numFeatures;
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UINT numClusters;
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double
rejectionThreshold;
//The classification threshold value
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double
gamma;
//The number of standard deviations to use for the threshold
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double
trainingMu;
//The average confidence value in the training data
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double
trainingSigma;
//The simga confidence value in the training data
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MatrixDouble
clusters;
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};
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}
//End of namespace GRT
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#endif //GRT_MINDISTMODEL_HEADER
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GRT::MinDistModel::~MinDistModel
~MinDistModel(void)
Definition:
MinDistModel.cpp:44
GRT::MinDistModel
Definition:
MinDistModel.h:37
GRT
Definition:
AdaBoost.cpp:25
GRT::MatrixDouble
Definition:
MatrixDouble.h:42
GRT::MinDistModel::MinDistModel
MinDistModel()
Definition:
MinDistModel.cpp:22
GRT::MinDistModel::operator=
MinDistModel & operator=(const MinDistModel &rhs)
Definition:
MinDistModel.cpp:46
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MinDistModel.h
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