Action: ANN
| Module | annfunc |
|---|---|
| Description | Usage |
| Calculates the ANN-function. |   |
Input
The arguments that serve as the input for this action are specified using one or more of the keywords in the following table.
| Keyword | Type | Description |
|---|---|---|
| ARG | scalar | the labels of the values from which the function is calculated |
Further details and examples
Text from manual goes here
Syntax
The following table describes the keywords and options that can be used with this action
| Keyword | Type | Default | Description |
|---|---|---|---|
| ARG | input | none | the labels of the values from which the function is calculated |
| PERIODIC | compulsory | none | if the output of your function is periodic then you should specify the periodicity of the function |
| NUM_LAYERS | compulsory | none | number of layers of the neural network |
| NUM_NODES | compulsory | none | numbers of nodes in each layer of the neural network |
| ACTIVATIONS | compulsory | none | activation functions for the neural network |
| NUMERICAL_DERIVATIVES | optional | false | calculate the derivatives for these quantities numerically |
| WEIGHTS | optional | not used | flattened weight arrays connecting adjacent layers, WEIGHTS0 represents flattened weight array connecting layer 0 and layer 1, WEIGHTS1 represents flattened weight array connecting layer 1 and layer 2, |
| BIASES | optional | not used | bias array for each layer of the neural network, BIASES0 represents bias array for layer 1, BIASES1 represents bias array for layer 2, |