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.
DataStructures Directory Reference

Files

file  ClassificationData.cpp [code]
 
file  ClassificationData.h [code]
 The ClassificationData is the main data structure for recording, labeling, managing, saving, and loading training data for supervised learning problems.
 
file  ClassificationSample.cpp [code]
 
file  ClassificationSample.h [code]
 This class stores the class label and raw data for a single labelled classification sample.
 
file  RegressionData.cpp [code]
 
file  RegressionData.h [code]
 The RegressionData is the main data structure for recording, labeling, managing, saving, and loading datasets that can be used to train and test the GRT supervised regression algorithms.
 
file  RegressionSample.cpp [code]
 
file  RegressionSample.h [code]
 This class stores the input vector and target vector for a single labelled regression instance.
 
file  TimeSeriesClassificationData.cpp [code]
 
file  TimeSeriesClassificationData.h [code]
 The TimeSeriesClassificationData is the main data structure for recording, labeling, managing, saving, and loading training data for supervised temporal learning problems. Unlike the ClassificationData, in which each sample consists of 1 N dimensional datum, a TimeSeriesClassificationData sample will consist of an N dimensional time series of length M. The length of each time series sample (i.e. M) can be different for each datum in the dataset.
 
file  TimeSeriesClassificationDataStream.cpp [code]
 
file  TimeSeriesClassificationDataStream.h [code]
 The TimeSeriesClassificationDataStream is the main data structure for recording, labeling, managing, saving, and loading datasets that can be used to test the continuous classification abilities of the GRT supervised temporal learning algorithms.
 
file  TimeSeriesClassificationSample.cpp [code]
 
file  TimeSeriesClassificationSample.h [code]
 This class stores the timeseries data for a single labelled timeseries classification sample.
 
file  TimeSeriesPositionTracker.h [code]
 This class can be used to track the class label, start and end indexs for labelled data.
 
file  UnlabelledData.cpp [code]
 
file  UnlabelledData.h [code]
 The UnlabelledData class is the main data container for supporting unsupervised learning.