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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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Public Member Functions | |
RegressionTreeNode () | |
virtual | ~RegressionTreeNode () |
virtual bool | predict (const VectorDouble &x) |
virtual bool | predict (const VectorDouble &x, VectorDouble &y) |
virtual bool | clear () |
virtual bool | print () const |
virtual Node * | deepCopyNode () const |
RegressionTreeNode * | deepCopyTree () const |
bool | set (const UINT nodeSize, const UINT featureIndex, const double threshold, const VectorDouble ®ressionData) |
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Node () | |
virtual | ~Node () |
virtual bool | getModel (ostream &stream) const |
virtual bool | saveToFile (fstream &file) const |
virtual bool | loadFromFile (fstream &file) |
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 |
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GRTBase (void) | |
virtual | ~GRTBase (void) |
bool | copyGRTBaseVariables (const GRTBase *GRTBase) |
string | getClassType () const |
string | getLastWarningMessage () const |
string | getLastErrorMessage () const |
string | getLastInfoMessage () const |
GRTBase * | getGRTBasePointer () |
const GRTBase * | getGRTBasePointer () const |
Protected Member Functions | |
virtual bool | saveParametersToFile (fstream &file) const |
virtual bool | loadParametersFromFile (fstream &file) |
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double | SQR (const double &x) const |
Protected Attributes | |
UINT | nodeSize |
UINT | featureIndex |
double | threshold |
VectorDouble | regressionData |
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string | nodeType |
UINT | depth |
UINT | nodeID |
UINT | predictedNodeID |
bool | isLeafNode |
Node * | parent |
Node * | leftChild |
Node * | rightChild |
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string | classType |
DebugLog | debugLog |
ErrorLog | errorLog |
InfoLog | infoLog |
TrainingLog | trainingLog |
TestingLog | testingLog |
WarningLog | warningLog |
Static Protected Attributes | |
static RegisterNode< RegressionTreeNode > | registerModule |
Additional Inherited Members | |
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typedef std::map< string, Node *(*)() > | StringNodeMap |
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static Node * | createInstanceFromString (string const &nodeType) |
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static string | getGRTVersion (bool returnRevision=true) |
static string | getGRTRevison () |
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static StringNodeMap * | getMap () |
Definition at line 37 of file RegressionTreeNode.h.
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inline |
Default Constructor. Sets all the pointers to NULL.
Definition at line 42 of file RegressionTreeNode.h.
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inlinevirtual |
Default Destructor. Cleans up any memory.
Definition at line 53 of file RegressionTreeNode.h.
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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.
Reimplemented from GRT::Node.
Definition at line 112 of file RegressionTreeNode.h.
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inlinevirtual |
This function returns a deep copy of the DecisionTreeNode and all it's children. The user is responsible for managing the dynamic data that is returned from this function as a pointer.
Reimplemented from GRT::Node.
Definition at line 162 of file RegressionTreeNode.h.
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inlineprotectedvirtual |
This loads the ClusterTreeNode parameters from a file.
fstream | &file: a reference to the file the parameters will be loaded from |
Reimplemented from GRT::Node.
Definition at line 251 of file RegressionTreeNode.h.
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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.
const | VectorDouble &x: the input vector that will be used for the prediction |
Reimplemented from GRT::Node.
Definition at line 67 of file RegressionTreeNode.h.
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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.
const | VectorDouble &x: the input vector that will be used for the prediction |
VectorDouble | &classLikelihoods: a reference to a vector that will store the class probabilities |
Reimplemented from GRT::Node.
Definition at line 85 of file RegressionTreeNode.h.
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inlinevirtual |
This functions prints the node data to std::out. It will recursively print all the child nodes.
Reimplemented from GRT::Node.
Definition at line 131 of file RegressionTreeNode.h.
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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.
fstream | &file: a reference to the file the parameters will be saved to |
Reimplemented from GRT::Node.
Definition at line 223 of file RegressionTreeNode.h.
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inline |
This function sets the Decision Tree Node.
const | UINT nodeSize: sets the node size, this is the number of training samples at that node |
const | UINT featureIndex: sets the index of the feature that should be used for the threshold spilt |
const | double threshold: set the threshold value used for the spilt |
const | VectorDouble ®ressionData: the regression data at this node |
Definition at line 207 of file RegressionTreeNode.h.