Structure Tag Name | Description |
---|---|
n_layers | A scalar integer defining the number of layers in the network. |
layers | A list with n_layers elements containing structures of type NN_Layer, where each structure encodes information about a different layer in the network. The input layer is layers(0) and the output layer is layers(n_layers-1). |
n_links | A scalar integer defining the number of links (weights) in the network. |
next_link | A scalar integer corresponding to the index of the last link in the network, plus 1. |
links | A list with n_links elements containing structures of type NN_Link, where each structure encodes information about a different link in the network. |
n_nodes | A scalar integer defining the number of nodes in the network. |
nodes | A list with n_nodes elements containing structures of type NN_Node, where each structure encodes information about a different node in the network. |
Structure Tag Name | Description |
---|---|
n_nodes | A scalar integer defining the number of nodes in the layer. |
nodes | An array of integers defining the index of each node in the layer. |
Structure Tag Name | Description |
---|---|
weight | A scalar float defining the numerical weight associated with the link. |
gradient | A scalar float defining the gradient (first derivative) associated with the weight. |
from_node | A scalar integer defining the index of the node that the link is coming from. |
to_node | A scalar integer defining the index of the node that the link is going to. |
Structure Tag Name | Description |
---|---|
activation_fcn_layer_id | A scalar integer defining the layer in which the node exists. |
n_inLinks | A scalar integer defining the number of links coming into the node. |
n_outLinks | A scalar integer defining the number of links going out of the node. |
inLinks | An array of integers defining the indices of the links coming into the node. |
outLinks | An array of integers defining the indices of the links going out of the node. |
gradient | A scalar float defining the gradient (first derivative) of the bias value associated with the node’s activation function. |
bias | A scalar float defining the bias value associated with the node’s activation function. The bias values are learned in the same way as weights are learned. |
ActivationFcn | A scalar integer 0-3 encoding the activation function type for the node, where: 0: Linear 1: Logistic 2: Hyperbolic-tangent 3: Squash Refer to Table 14-12: Activation Functions and Their Derivatives in Chapter 14: Data Mining in the PV‑WAVE IMSL Statistics Reference. |
Structure member | Description |
---|---|
network.n_layers | Number of layers in network. Layers are numbered starting at 0 for the input layer. |
network.n_nodes | Total number of nodes in network, including the input attributes. |
network.n_links | Total number of links or connections between input attributes and perceptrons and between perceptrons from layer to layer. |
network.layers(0) | Input layer with n_inputs attributes. |
network.layers(network.n_layers-1) | Output layer with n_outputs perceptrons. |
network.layers(0).n_nodes | n_inputs (number of input attributes). |
network.layers(ffnet.n_layers-1).n_nodes | n_outputs (number of output perceptrons). |
network.layers(1).n_nodes | Number of output perceptrons in first hidden layer. |
network.n_links(i).weight | Initial weight for the ith link in network. After the training has completed the structure menber contains the weight used for forecasting. |
network.n_nodes(i).bias | Initial bias value for the ith node. After the training has completed the bias value is updated. |