# demard

## Purpose

Automatic relevance determination using the MLP.

## Synopsis

    demmlp1

## Description

This script demonstrates the technique of automatic relevance determination (ARD) using a synthetic problem having three input variables: `x1` is sampled uniformly from the range (0,1) and has a low level of added Gaussian noise, `x2` is a copy of `x1` with a higher level of added noise, and `x3` is sampled randomly from a Gaussian distribution. The single target variable is determined by `sin(2*pi*x1)` with additive Gaussian noise. Thus `x1` is very relevant for determining the target value, `x2` is of some relevance, while `x3` is irrelevant. The prior over weights is given by the ARD Gaussian prior with a separate hyper-parameter for the group of weights associated with each input. A multi-layer perceptron is trained on this data, with re-estimation of the hyper-parameters using `evidence`. The final values for the hyper-parameters reflect the relative importance of the three inputs.

## See Also

`demmlp1`, `demev1`, `mlp`, `evidence`

Pages: Index

Copyright (c) Ian T Nabney (1996-9)