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NeuralNet Functions

DADiSP/NeuralNet includes several functions to create, apply and analyze neural networks.

NeuralNet Functions

applynet Apply a neural network to new input data
innorm Normalize network inputs to +/- 1.0 using mean and variance
inscale Linearly scale network inputs to +/- 1.0 using min and max
makecvnet Create a neural network with cross verification
makenet Create a neural network
nnoptrun Extract neural network weights based on best error statistics
nnrun Extract a particular set of post training data for a run
nnseeds Extract neural network random seed values
nnweight Extract neural network weights
outnorm Normalize network output data using a reference series
outscale Linearly scale network output data using a reference series


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