GestureRecognitionToolkit
Version: 0.2.5
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
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#include <ClusterTreeNode.h>
Public Member Functions | |
ClusterTreeNode () | |
virtual | ~ClusterTreeNode () |
virtual bool | predict_ (VectorFloat &x) override |
virtual bool | predict_ (VectorFloat &x, VectorFloat &y) override |
virtual bool | clear () override |
virtual bool | print () const override |
virtual Node * | deepCopy () const override |
ClusterTreeNode * | deepCopyTree () 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 (const std::string id="Node") | |
virtual | ~Node () |
virtual bool | computeFeatureWeights (VectorFloat &weights) const |
virtual bool | computeLeafNodeWeights (MatrixFloat &weights) const |
virtual bool | getModel (std::ostream &stream) const override |
virtual bool | save (std::fstream &file) const override |
virtual bool | load (std::fstream &file) override |
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 MLBase | |
MLBase (const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET) | |
virtual | ~MLBase (void) |
bool | copyMLBaseVariables (const MLBase *mlBase) |
virtual bool | train (ClassificationData trainingData) |
virtual bool | train_ (ClassificationData &trainingData) |
virtual bool | train (RegressionData trainingData) |
virtual bool | train_ (RegressionData &trainingData) |
virtual bool | train (RegressionData trainingData, RegressionData validationData) |
virtual bool | train_ (RegressionData &trainingData, RegressionData &validationData) |
virtual bool | train (TimeSeriesClassificationData trainingData) |
virtual bool | train_ (TimeSeriesClassificationData &trainingData) |
virtual bool | train (ClassificationDataStream trainingData) |
virtual bool | train_ (ClassificationDataStream &trainingData) |
virtual bool | train (UnlabelledData trainingData) |
virtual bool | train_ (UnlabelledData &trainingData) |
virtual bool | train (MatrixFloat data) |
virtual bool | train_ (MatrixFloat &data) |
virtual bool | predict (VectorFloat inputVector) |
virtual bool | predict (MatrixFloat inputMatrix) |
virtual bool | predict_ (MatrixFloat &inputMatrix) |
virtual bool | map (VectorFloat inputVector) |
virtual bool | map_ (VectorFloat &inputVector) |
virtual bool | reset () |
virtual bool | save (const std::string &filename) const |
virtual bool | load (const std::string &filename) |
GRT_DEPRECATED_MSG ("saveModelToFile(std::string filename) is deprecated, use save(const std::string &filename) instead", virtual bool saveModelToFile(const std::string &filename) const ) | |
GRT_DEPRECATED_MSG ("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const ) | |
GRT_DEPRECATED_MSG ("loadModelFromFile(std::string filename) is deprecated, use load(const std::string &filename) instead", virtual bool loadModelFromFile(const std::string &filename)) | |
GRT_DEPRECATED_MSG ("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file)) | |
virtual std::string | getModelAsString () const |
DataType | getInputType () const |
DataType | getOutputType () const |
BaseType | getType () const |
UINT | getNumInputFeatures () const |
UINT | getNumInputDimensions () const |
UINT | getNumOutputDimensions () const |
UINT | getMinNumEpochs () const |
UINT | getMaxNumEpochs () const |
UINT | getBatchSize () const |
UINT | getNumRestarts () const |
UINT | getValidationSetSize () const |
UINT | getNumTrainingIterationsToConverge () const |
Float | getMinChange () const |
Float | getLearningRate () const |
Float | getRMSTrainingError () const |
GRT_DEPRECATED_MSG ("getRootMeanSquaredTrainingError() is deprecated, use getRMSTrainingError() instead", Float getRootMeanSquaredTrainingError() const ) | |
Float | getTotalSquaredTrainingError () const |
Float | getRMSValidationError () const |
Float | getValidationSetAccuracy () const |
VectorFloat | getValidationSetPrecision () const |
VectorFloat | getValidationSetRecall () const |
bool | getUseValidationSet () const |
bool | getRandomiseTrainingOrder () const |
bool | getTrained () const |
GRT_DEPRECATED_MSG ("getModelTrained() is deprecated, use getTrained() instead", bool getModelTrained() const ) | |
bool | getConverged () const |
bool | getScalingEnabled () const |
bool | getIsBaseTypeClassifier () const |
bool | getIsBaseTypeRegressifier () const |
bool | getIsBaseTypeClusterer () const |
bool | getTrainingLoggingEnabled () const |
bool | getTestingLoggingEnabled () const |
bool | enableScaling (const bool useScaling) |
bool | setMaxNumEpochs (const UINT maxNumEpochs) |
bool | setBatchSize (const UINT batchSize) |
bool | setMinNumEpochs (const UINT minNumEpochs) |
bool | setNumRestarts (const UINT numRestarts) |
bool | setMinChange (const Float minChange) |
bool | setLearningRate (const Float learningRate) |
bool | setUseValidationSet (const bool useValidationSet) |
bool | setValidationSetSize (const UINT validationSetSize) |
bool | setRandomiseTrainingOrder (const bool randomiseTrainingOrder) |
bool | setTrainingLoggingEnabled (const bool loggingEnabled) |
bool | setTestingLoggingEnabled (const bool loggingEnabled) |
bool | registerTrainingResultsObserver (Observer< TrainingResult > &observer) |
bool | registerTestResultsObserver (Observer< TestInstanceResult > &observer) |
bool | removeTrainingResultsObserver (const Observer< TrainingResult > &observer) |
bool | removeTestResultsObserver (const Observer< TestInstanceResult > &observer) |
bool | removeAllTrainingObservers () |
bool | removeAllTestObservers () |
bool | notifyTrainingResultsObservers (const TrainingResult &data) |
bool | notifyTestResultsObservers (const TestInstanceResult &data) |
MLBase * | getMLBasePointer () |
const MLBase * | getMLBasePointer () const |
Vector< TrainingResult > | getTrainingResults () const |
Public Member Functions inherited from GRTBase | |
GRTBase (const std::string &id="") | |
virtual | ~GRTBase (void) |
bool | copyGRTBaseVariables (const GRTBase *GRTBase) |
GRT_DEPRECATED_MSG ("getClassType is deprecated, use getId() instead!", std::string getClassType() const ) | |
std::string | getId () 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) |
bool | setDebugLoggingEnabled (const bool loggingEnabled) |
GRTBase * | getGRTBasePointer () |
const GRTBase * | getGRTBasePointer () const |
Float | scale (const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false) |
Float | SQR (const Float &x) const |
Public Member Functions inherited from Observer< TrainingResult > | |
virtual void | notify (const TrainingResult &data) |
Public Member Functions inherited from Observer< TestInstanceResult > | |
virtual void | notify (const TestInstanceResult &data) |
Protected Member Functions | |
virtual bool | saveParametersToFile (std::fstream &file) const override |
virtual bool | loadParametersFromFile (std::fstream &file) override |
Protected Member Functions inherited from MLBase | |
bool | saveBaseSettingsToFile (std::fstream &file) const |
bool | loadBaseSettingsFromFile (std::fstream &file) |
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 |
Node * | parent |
Node * | leftChild |
Node * | rightChild |
Protected Attributes inherited from MLBase | |
bool | trained |
bool | useScaling |
bool | converged |
DataType | inputType |
DataType | outputType |
BaseType | baseType |
UINT | numInputDimensions |
UINT | numOutputDimensions |
UINT | numTrainingIterationsToConverge |
UINT | minNumEpochs |
UINT | maxNumEpochs |
UINT | batchSize |
UINT | validationSetSize |
UINT | numRestarts |
Float | learningRate |
Float | minChange |
Float | rmsTrainingError |
Float | rmsValidationError |
Float | totalSquaredTrainingError |
Float | validationSetAccuracy |
bool | useValidationSet |
bool | randomiseTrainingOrder |
VectorFloat | validationSetPrecision |
VectorFloat | validationSetRecall |
Random | random |
Vector< TrainingResult > | trainingResults |
TrainingResultsObserverManager | trainingResultsObserverManager |
TestResultsObserverManager | testResultsObserverManager |
TrainingLog | trainingLog |
TestingLog | testingLog |
Protected Attributes inherited from GRTBase | |
std::string | classId |
Stores the name of the class (e.g., MinDist) | |
DebugLog | debugLog |
ErrorLog | errorLog |
InfoLog | infoLog |
WarningLog | warningLog |
Static Protected Attributes | |
static RegisterNode< ClusterTreeNode > | registerModule |
Additional Inherited Members | |
Public Types inherited from Node | |
typedef std::map< std::string, Node *(*)() > | StringNodeMap |
Public Types inherited from MLBase | |
enum | BaseType { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER, PRE_PROCSSING, POST_PROCESSING, FEATURE_EXTRACTION, CONTEXT } |
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 () |
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.
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inline |
Default Constructor. Sets all the pointers to NULL.
Definition at line 41 of file ClusterTreeNode.h.
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inlinevirtual |
Default Destructor. Cleans up any memory.
Definition at line 52 of file ClusterTreeNode.h.
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inlineoverridevirtual |
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 Node.
Definition at line 112 of file ClusterTreeNode.h.
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inlineoverridevirtual |
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.
Reimplemented from Node.
Definition at line 158 of file ClusterTreeNode.h.
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This function returns the cluster label.
Definition at line 226 of file ClusterTreeNode.h.
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This function returns the featureIndex, this is index in the input data that the decision threshold is computed on.
Definition at line 208 of file ClusterTreeNode.h.
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inline |
This function returns the nodeSize, this is the number of training samples that reached the node during the training phase.
Definition at line 199 of file ClusterTreeNode.h.
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inline |
This function returns the threshold, this is the value used to compute the decision threshold.
Definition at line 217 of file ClusterTreeNode.h.
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inlineoverrideprotectedvirtual |
This loads the ClusterTreeNode parameters from a file.
file | a reference to the file the parameters will be loaded from |
Reimplemented from Node.
Definition at line 278 of file ClusterTreeNode.h.
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inlineoverridevirtual |
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.
x | the input Vector that will be used for the prediction |
Reimplemented from Node.
Definition at line 66 of file ClusterTreeNode.h.
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inlineoverridevirtual |
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.
x | the input Vector that will be used for the prediction |
classLikelihoods | a reference to a Vector that will store the class probabilities |
Reimplemented from Node.
Definition at line 84 of file ClusterTreeNode.h.
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inlineoverridevirtual |
This functions prints the node data to std::out. It will recursively print all the child nodes.
Reimplemented from Node.
Definition at line 131 of file ClusterTreeNode.h.
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inlineoverrideprotectedvirtual |
This saves the ClusterTreeNode custom parameters to a file. It will be called automatically by the Node base class if the save function is called.
file | a reference to the file the parameters will be saved to |
Reimplemented from Node.
Definition at line 255 of file ClusterTreeNode.h.
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inline |
This function sets the Cluster Tree Node.
nodeSize | sets the node size, this is the number of training samples at that node |
featureIndex | sets the index of the feature that should be used for the threshold spilt |
threshold | set the threshold value used for the spilt |
clusterLabel | the cluster label for this node |
Definition at line 239 of file ClusterTreeNode.h.