Interface Summary Interface Description NeuralNetwork.MonitorInterface
Monitorallows to plug a monitor to a Neural Network instance, and inform the monitor about the progress of the training activity.
Class Summary Class Description BackpropagationNetBackpropagation is a supervised learning algorithm and is mainly used by Multi-Layer-Perceptrons to change the weights connected to the net's hidden neuron layer(s). Example InputMatrixInput matrix. InputValue KohonenFeatureMapKohonenFeatureMap. MapNeuron NeuralNetworkClass
NeuralNetworkimplements a back-propagation neural network, with one input layer, one hidden layer and one output layer.
Backupis an opaque class that encapsulates a snapshot of a NeuralNetwork internal memory (its weights).
NeuronThis cluss build a single neuron. NeuronLayer NeuronMatrix PatternThe pattern file of a Backpropagation Net contains the input and target patterns for the net. ThreeD WeightMatrixThe connection structure between two neuron layers of a neural net.
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