GestureRecognitionToolkit  Version: 0.1.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
ClusterTreeNode Class Reference

#include <ClusterTreeNode.h>

Inheritance diagram for ClusterTreeNode:
Node GRTBase

Public Member Functions

 ClusterTreeNode ()
 
virtual ~ClusterTreeNode ()
 
virtual bool predict (const VectorFloat &x)
 
virtual bool predict (const VectorFloat &x, VectorFloat &y)
 
virtual bool clear ()
 
virtual bool print () const
 
virtual NodedeepCopyNode () const
 
ClusterTreeNodedeepCopyTree () const
 
UINT getNodeSize () const
 
UINT getFeatureIndex () const
 
Float getThreshold () const
 
UINT getClusterLabel () const
 
bool set (const UINT nodeSize, const UINT featureIndex, const Float threshold, const UINT clusterLabel)
 
- Public Member Functions inherited from Node
 Node ()
 
virtual ~Node ()
 
virtual bool computeFeatureWeights (VectorFloat &weights) const
 
virtual bool computeLeafNodeWeights (MatrixFloat &weights) const
 
virtual bool getModel (std::ostream &stream) const
 
virtual bool saveToFile (std::fstream &file) const
 
virtual bool loadFromFile (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
 
NodegetParent () const
 
NodegetLeftChild () const
 
NodegetRightChild () 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)
 
NodecreateNewInstance () 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)
 
GRTBasegetGRTBasePointer ()
 
const GRTBasegetGRTBasePointer () const
 

Protected Member Functions

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 clusterLabel
 
UINT nodeSize
 
UINT featureIndex
 
Float threshold
 
- Protected Attributes inherited from Node
std::string nodeType
 
UINT depth
 
UINT nodeID
 
UINT predictedNodeID
 
bool isLeafNode
 
Nodeparent
 
NodeleftChild
 
NoderightChild
 
- 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< ClusterTreeNoderegisterModule
 

Additional Inherited Members

- Public Types inherited from Node
typedef std::map< std::string, Node *(*)() > StringNodeMap
 
- Static Public Member Functions inherited from Node
static NodecreateInstanceFromString (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 StringNodeMapgetMap ()
 

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 36 of file ClusterTreeNode.h.

Constructor & Destructor Documentation

ClusterTreeNode::ClusterTreeNode ( )
inline

Default Constructor. Sets all the pointers to NULL.

Definition at line 41 of file ClusterTreeNode.h.

virtual ClusterTreeNode::~ClusterTreeNode ( )
inlinevirtual

Default Destructor. Cleans up any memory.

Definition at line 52 of file ClusterTreeNode.h.

Member Function Documentation

virtual bool ClusterTreeNode::clear ( )
inlinevirtual

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 Node.

Definition at line 112 of file ClusterTreeNode.h.

virtual Node* ClusterTreeNode::deepCopyNode ( ) const
inlinevirtual

This function returns a deep copy of the ClusterTreeNode 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 ClusterTreeNode, or NULL if the deep copy was not successful

Reimplemented from Node.

Definition at line 158 of file ClusterTreeNode.h.

UINT ClusterTreeNode::getClusterLabel ( ) const
inline

This function returns the cluster label.

Returns
returns the cluster label.

Definition at line 226 of file ClusterTreeNode.h.

UINT ClusterTreeNode::getFeatureIndex ( ) const
inline

This function returns the featureIndex, this is index in the input data that the decision threshold is computed on.

Returns
returns the featureIndex

Definition at line 208 of file ClusterTreeNode.h.

UINT ClusterTreeNode::getNodeSize ( ) const
inline

This function returns the nodeSize, this is the number of training samples that reached the node during the training phase.

Returns
returns the nodeSize

Definition at line 199 of file ClusterTreeNode.h.

Float ClusterTreeNode::getThreshold ( ) const
inline

This function returns the threshold, this is the value used to compute the decision threshold.

Returns
returns the threshold

Definition at line 217 of file ClusterTreeNode.h.

virtual bool ClusterTreeNode::loadParametersFromFile ( std::fstream &  file)
inlineprotectedvirtual

This loads the ClusterTreeNode 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 Node.

Definition at line 278 of file ClusterTreeNode.h.

virtual bool ClusterTreeNode::predict ( const VectorFloat x)
inlinevirtual

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. The threshold and featureIndex can be set by training the node through the DecisionTree class.

Parameters
constVectorFloat &x: the 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 66 of file ClusterTreeNode.h.

virtual bool ClusterTreeNode::predict ( const VectorFloat x,
VectorFloat y 
)
inlinevirtual

This function recursively predicts if the probability of the input Vector. If this node is a leaf node, then the class likelihoods are equal to the class probabilities at the leaf node. If this node is not a leaf node, then this function will recursively call the predict function on either the left or right children until a leaf node is reached.

NOTE: The threshold, featureIndex and classProbabilities should be set first BEFORE this function is called. The threshold, featureIndex and classProbabilities can be set by training the node through the DecisionTree class.

Parameters
constVectorFloat &x: the input Vector that will be used for the prediction
VectorFloat&classLikelihoods: a reference to a Vector that will store the class probabilities
Returns
returns true if the input is greater than or equal to the nodes threshold, false otherwise

Reimplemented from Node.

Definition at line 84 of file ClusterTreeNode.h.

virtual bool ClusterTreeNode::print ( ) const
inlinevirtual

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 131 of file ClusterTreeNode.h.

virtual bool ClusterTreeNode::saveParametersToFile ( std::fstream &  file) const
inlineprotectedvirtual

This saves the ClusterTreeNode custom parameters to a file. It will be called automatically by the Node base class if the saveToFile 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 Node.

Definition at line 255 of file ClusterTreeNode.h.

bool ClusterTreeNode::set ( const UINT  nodeSize,
const UINT  featureIndex,
const Float  threshold,
const UINT  clusterLabel 
)
inline

This function sets the Cluster Tree Node.

Parameters
nodeSizesets the node size, this is the number of training samples at that node
featureIndexsets the index of the feature that should be used for the threshold spilt
thresholdset the threshold value used for the spilt
clusterLabelthe cluster label for this node
Returns
returns true if the node was set, false otherwise

Definition at line 239 of file ClusterTreeNode.h.


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