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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This class implements a Radial Basis Function Weak Classifier. The Radial Basis Function (RBF) class fits an RBF to the weighted training data so as to maximize the number of positive training samples that are inside a specific region of the RBF (this region is set by the GRT::RadialBasisFunction::positiveClassificationThreshold parameter). After the RBF has been trained, it will output 1 if the input data is inside the RBF positive classification region, otherwise it will output 0. More...
#include "WeakClassifier.h"
Go to the source code of this file.
Classes | |
class | RadialBasisFunction |
This class implements a Radial Basis Function Weak Classifier. The Radial Basis Function (RBF) class fits an RBF to the weighted training data so as to maximize the number of positive training samples that are inside a specific region of the RBF (this region is set by the GRT::RadialBasisFunction::positiveClassificationThreshold parameter). After the RBF has been trained, it will output 1 if the input data is inside the RBF positive classification region, otherwise it will output 0.
Definition in file RadialBasisFunction.h.