The Neural Network Package

Neural Network Types

Feedforward Neural Networks - Feedforward neural networks are used for general function approximation, classification, and estimation of dynamic models and time series.

Radial Basis Function Networks - Like feedforward neural networks, radial basis function networks are also used for general function approximation, classification, and estimation of dynamic models and time series.

Dynamic Neural Networks - Dynamic neural networks are based on either feedforward neural networks or radial basis function networks, and they are used for estimation of dynamic models and time series.

Perceptrons - The perceptron is the simplest type of neural network and it is typically used for classification.

Vector Quantization Networks - Vector quantization (VQ) networks are used for classification.

Unsupervised Networks - Unsupervised networks are used to find structures in the data.

Hopfield Networks - Hopfield networks, also called associative networks, are used for classification.

From the package palette you access all the functions of the package, their options and the entire documentation.

Neural Network Palette