Index
The activation functions used for the neurons during training. This callback function can be called during training when using neural_net::train_on_data, neural_net::train_on_file or neural_net::cascadetrain_on_data. Trains on an entire dataset, for a period of time using the Cascade2 training algorithm. Does the same as cascadetrain_on_data, but reads the training data directly from a file. Clears scaling parameters. Describes a connection between two neurons and its weight Constructs a backpropagation neural network from a configuration file, which have been saved by save. Creates a standard backpropagation neural network, which is not fully connected and which also has shortcut connections. Just like create_shortcut, but with an array of layer sizes instead of individual parameters. Creates a standard backpropagation neural network, which is not fully connected. Just like create_sparse, but with an array of layer sizes instead of individual parameters. Creates a standard fully connected backpropagation neural network. Just like create_standard, but with an array of layer sizes instead of individual parameters. Creates the training data struct from a user supplied function. Scale data in input vector after get it from ann based on previously calculated parameters. Scale data in output vector after get it from ann based on previously calculated parameters. Descale input and output data based on previously calculated parameters. Destructs the entire network. Destructs the training data. Error function used during training. Standard linear error function. Tanh error function, usually better but can require a lower learning rate. |