## Multi-Layer Perceptron

MLP is a model of feed-forward Artificial Neural Networks composed by number of separate (hidden) layers. Information is passed from one layer to the next following a given activation function. Training of MLP is done by back-propagation.
More information on Wikipedia.
Parameters:

- # Neurons: number of neurons per hidden layer; input and output nodes are not counted
- # Layers: number of hidden layers
- Activation function: output function for all neurons in the network

- sigmoid: beta*(1-exp(-alpha*x)) / (1 + exp(-alpha*x))
- gaussian: beta*exp(-alpha*x*x)