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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