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WTALearningFunction - Class in kohonen

Winner Takes All - algorytm there only winnig neuron weights are changed according to the formula w(k+1) = w(k) + n * (x-w) where
w(k+1) - neuron weight in k +1 interation
w(k) - neruon weight for k iteration
n - value of learning function factor for k iteriation
x - learning vector od data w - neuron weight

WTALearningFunction(NetworkModel, int, MetricModel, LearningDataModel, LearningFactorFunctionalModel) - Constructor for class kohonen.WTALearningFunction

Creates a new instance of WTALearningFunction.

WTALearningFunctionWithTired - Class in kohonen

WTALearningFunctionWithTired class - learnig class used to learn neurons with tiredness

WTALearningFunctionWithTired(NetworkModel, int, MetricModel, LearningDataModel, LearningFactorFunctionalModel) - Constructor for class kohonen.WTALearningFunctionWithTired

Creates a new instance of WTALearningFunction.

WTMLearningFunction - Class in kohonen

Winner Takes Most - algorytm where winnig neuron and neurons in neighboorhood weights are changed according to the formula w(k+1) = w(k) + n *N(i,x)* (x-w) where
w(k+1) - neuron weight in k +1 interation
w(k) - neruon weight for k iteration
n - value of learning function factor for k iteriation
N(i,x) - value of neighboorhood function for i - specified neuron x - learning vector od data w - neuron weight

WTMLearningFunction(NetworkModel, int, MetricModel, LearningDataModel, LearningFactorFunctionalModel, NeighbourhoodFunctionModel) - Constructor for class kohonen.WTMLearningFunction

Creates a new instance of WTMLearningFunction

WTMLearningFunctionWithTired - Class in kohonen

WTMLearningFunctionWithTired class - learnig class used to learn neuron with tiredness

WTMLearningFunctionWithTired(NetworkModel, int, MetricModel, LearningDataModel, LearningFactorFunctionalModel, NeighbourhoodFunctionModel) - Constructor for class kohonen.WTMLearningFunctionWithTired

Creates a new instance of WTMLearningFunction