GestureRecognitionToolkit  Version: 0.2.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
Public Member Functions | Protected Member Functions | Protected Attributes | Static Protected Attributes | List of all members
DecisionTreeTripleFeatureNode Class Reference

#include <DecisionTreeTripleFeatureNode.h>

Inheritance diagram for DecisionTreeTripleFeatureNode:
DecisionTreeNode Node GRTBase

Public Member Functions

 DecisionTreeTripleFeatureNode ()
 
virtual ~DecisionTreeTripleFeatureNode ()
 
virtual bool predict (const VectorFloat &x)
 
virtual bool clear ()
 
virtual bool print () const
 
virtual bool getModel (std::ostream &stream) const
 
virtual Node * deepCopyNode () const
 
DecisionTreeTripleFeatureNode * deepCopy () const
 
UINT getFeatureIndexA () const
 
UINT getFeatureIndexB () const
 
UINT getFeatureIndexC () const
 
bool set (const UINT nodeSize, const UINT featureIndexA, const UINT featureIndexB, const UINT featureIndexC, const VectorFloat &classProbabilities)
 
- Public Member Functions inherited from DecisionTreeNode
 DecisionTreeNode ()
 
virtual ~DecisionTreeNode ()
 
virtual bool predict (const VectorFloat &x, VectorFloat &classLikelihoods)
 
virtual bool computeBestSpilt (const UINT &trainingMode, const UINT &numSplittingSteps, const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError)
 
DecisionTreeNode * deepCopy () const
 
UINT getNodeSize () const
 
UINT getNumClasses () const
 
VectorFloat getClassProbabilities () const
 
bool setLeafNode (const UINT nodeSize, const VectorFloat &classProbabilities)
 
bool setNodeSize (const UINT nodeSize)
 
bool setClassProbabilities (const VectorFloat &classProbabilities)
 
- Public Member Functions inherited from Node
 Node ()
 
virtual ~Node ()
 
virtual bool computeFeatureWeights (VectorFloat &weights) const
 
virtual bool computeLeafNodeWeights (MatrixFloat &weights) const
 
virtual bool save (std::fstream &file) const
 
virtual bool load (std::fstream &file)
 
std::string getNodeType () const
 
UINT getDepth () const
 
UINT getNodeID () const
 
UINT getPredictedNodeID () const
 
UINT getMaxDepth () const
 
bool getIsLeafNode () const
 
bool getHasParent () const
 
bool getHasLeftChild () const
 
bool getHasRightChild () const
 
Node * getParent () const
 
Node * getLeftChild () const
 
Node * getRightChild () const
 
bool initNode (Node *parent, const UINT depth, const UINT nodeID, const bool isLeafNode=false)
 
bool setParent (Node *parent)
 
bool setLeftChild (Node *leftChild)
 
bool setRightChild (Node *rightChild)
 
bool setDepth (const UINT depth)
 
bool setNodeID (const UINT nodeID)
 
bool setIsLeafNode (const bool isLeafNode)
 
Node * createNewInstance () const
 
- Public Member Functions inherited from GRTBase
 GRTBase (void)
 
virtual ~GRTBase (void)
 
bool copyGRTBaseVariables (const GRTBase *GRTBase)
 
std::string getClassType () const
 
std::string getLastWarningMessage () const
 
std::string getLastErrorMessage () const
 
std::string getLastInfoMessage () const
 
bool setInfoLoggingEnabled (const bool loggingEnabled)
 
bool setWarningLoggingEnabled (const bool loggingEnabled)
 
bool setErrorLoggingEnabled (const bool loggingEnabled)
 
GRTBase * getGRTBasePointer ()
 
const GRTBase * getGRTBasePointer () const
 

Protected Member Functions

virtual bool computeBestSpiltBestIterativeSpilt (const UINT &numSplittingSteps, const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError)
 
virtual bool computeBestSpiltBestRandomSpilt (const UINT &numSplittingSteps, const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError)
 
bool computeBestSpilt (const UINT &numSplittingSteps, const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError)
 
virtual bool saveParametersToFile (std::fstream &file) const
 
virtual bool loadParametersFromFile (std::fstream &file)
 
- Protected Member Functions inherited from GRTBase
Float SQR (const Float &x) const
 

Protected Attributes

UINT featureIndexA
 
UINT featureIndexB
 
UINT featureIndexC
 
- Protected Attributes inherited from DecisionTreeNode
UINT nodeSize
 
VectorFloat classProbabilities
 
- Protected Attributes inherited from Node
std::string nodeType
 
UINT depth
 
UINT nodeID
 
UINT predictedNodeID
 
bool isLeafNode
 
Node * parent
 
Node * leftChild
 
Node * rightChild
 
- Protected Attributes inherited from GRTBase
std::string classType
 
DebugLog debugLog
 
ErrorLog errorLog
 
InfoLog infoLog
 
TrainingLog trainingLog
 
TestingLog testingLog
 
WarningLog warningLog
 

Static Protected Attributes

static RegisterNode< DecisionTreeTripleFeatureNode > registerModule
 
- Static Protected Attributes inherited from DecisionTreeNode
static RegisterNode< DecisionTreeNode > registerModule
 

Additional Inherited Members

- Public Types inherited from Node
typedef std::map< std::string, Node *(*)() > StringNodeMap
 
- Static Public Member Functions inherited from DecisionTreeNode
static UINT getClassLabelIndexValue (UINT classLabel, const Vector< UINT > &classLabels)
 
- Static Public Member Functions inherited from Node
static Node * createInstanceFromString (std::string const &nodeType)
 
- Static Public Member Functions inherited from GRTBase
static std::string getGRTVersion (bool returnRevision=true)
 
static std::string getGRTRevison ()
 
- Static Protected Member Functions inherited from Node
static StringNodeMap * getMap ()
 

Detailed Description

GRT MIT License Copyright (c) <2012> <Nicholas Gillian, Media Lab, MIT>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Definition at line 37 of file DecisionTreeTripleFeatureNode.h.

Constructor & Destructor Documentation

DecisionTreeTripleFeatureNode::DecisionTreeTripleFeatureNode ( )

Default Constructor. Sets all the pointers to NULL.

Definition at line 10 of file DecisionTreeTripleFeatureNode.cpp.

DecisionTreeTripleFeatureNode::~DecisionTreeTripleFeatureNode ( )
virtual

Default Destructor. Cleans up any memory.

Definition at line 18 of file DecisionTreeTripleFeatureNode.cpp.

Member Function Documentation

bool DecisionTreeTripleFeatureNode::clear ( )
virtual

This functions cleans up any dynamic memory assigned by the node. It will recursively clear the memory for the left and right child nodes.

Returns
returns true of the node was cleared correctly, false otherwise

Reimplemented from DecisionTreeNode.

Definition at line 29 of file DecisionTreeTripleFeatureNode.cpp.

DecisionTreeTripleFeatureNode * DecisionTreeTripleFeatureNode::deepCopy ( ) const

This function returns a deep copy of the DecisionTreeTripleFeatureNode and all it's children. The user is responsible for managing the dynamic data that is returned from this function as a pointer.

Returns
returns a pointer to a deep copy of the DecisionTreeTripleFeatureNode, or NULL if the deep copy was not successful

Definition at line 118 of file DecisionTreeTripleFeatureNode.cpp.

Node * DecisionTreeTripleFeatureNode::deepCopyNode ( ) const
virtual

This function returns a deep copy of the DecisionTreeTripleFeatureNode and all it's children. The user is responsible for managing the dynamic data that is returned from this function as a pointer.

Returns
returns a pointer to a deep copy of the DecisionTreeTripleFeatureNode, or NULL if the deep copy was not successful

Reimplemented from DecisionTreeNode.

Definition at line 84 of file DecisionTreeTripleFeatureNode.cpp.

UINT DecisionTreeTripleFeatureNode::getFeatureIndexA ( ) const

This function returns the first featureIndex.

Returns
returns the first featureIndex

Definition at line 122 of file DecisionTreeTripleFeatureNode.cpp.

UINT DecisionTreeTripleFeatureNode::getFeatureIndexB ( ) const

This function returns the second featureIndex.

Returns
returns the second featureIndex

Definition at line 126 of file DecisionTreeTripleFeatureNode.cpp.

UINT DecisionTreeTripleFeatureNode::getFeatureIndexC ( ) const

This function returns the third featureIndex.

Returns
returns the third featureIndex

Definition at line 130 of file DecisionTreeTripleFeatureNode.cpp.

bool DecisionTreeTripleFeatureNode::getModel ( std::ostream &  stream) const
virtual

This function adds the current model to the formatted stream. This function should be overwritten by the derived class.

Parameters
filea reference to the stream the model will be added to
Returns
returns true if the model was added successfully, false otherwise

Reimplemented from DecisionTreeNode.

Definition at line 53 of file DecisionTreeTripleFeatureNode.cpp.

bool DecisionTreeTripleFeatureNode::loadParametersFromFile ( std::fstream &  file)
protectedvirtual

This loads the Decision Tree Node parameters from a file.

Parameters
filea reference to the file the parameters will be loaded from
Returns
returns true if the model was loaded successfully, false otherwise

Reimplemented from DecisionTreeNode.

Definition at line 256 of file DecisionTreeTripleFeatureNode.cpp.

bool DecisionTreeTripleFeatureNode::predict ( const VectorFloat &  x)
virtual

This function predicts if the input is greater than or equal to the nodes threshold. If the input is greater than or equal to the nodes threshold then this function will return true, otherwise it will return false.

NOTE: The threshold and featureIndex should be set first BEFORE this function is called.

Parameters
xthe input Vector that will be used for the prediction
Returns
returns true if the input is greater than or equal to the nodes threshold, false otherwise

Reimplemented from Node.

Definition at line 22 of file DecisionTreeTripleFeatureNode.cpp.

bool DecisionTreeTripleFeatureNode::print ( ) const
virtual

This functions prints the node data to std::out. It will recursively print all the child nodes.

Returns
returns true if the data was printed correctly, false otherwise

Reimplemented from Node.

Definition at line 41 of file DecisionTreeTripleFeatureNode.cpp.

bool DecisionTreeTripleFeatureNode::saveParametersToFile ( std::fstream &  file) const
protectedvirtual

This saves the DecisionTreeNode custom parameters to a file. It will be called automatically by the Node base class if the save function is called.

Parameters
filea reference to the file the parameters will be saved to
Returns
returns true if the model was saved successfully, false otherwise

Reimplemented from DecisionTreeNode.

Definition at line 234 of file DecisionTreeTripleFeatureNode.cpp.

bool DecisionTreeTripleFeatureNode::set ( const UINT  nodeSize,
const UINT  featureIndexA,
const UINT  featureIndexB,
const UINT  featureIndexC,
const VectorFloat &  classProbabilities 
)

This function sets the Decision Tree Threshold Node.

Parameters
nodeSizesets the node size, this is the number of training samples at that node
featureIndexAsets the first index of the feature that should be used for the threshold spilt
featureIndexBsets the second index of the feature that should be used for the threshold spilt
featureIndexCsets the third index of the feature that should be used for the threshold spilt
classProbabilitiesthe Vector of class probabilities at this node
Returns
returns true if the node was set, false otherwise

Definition at line 134 of file DecisionTreeTripleFeatureNode.cpp.

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