| ### Chapter 15 - Generalization Prediction and Assessment
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Russell D. Reed and Robert J. Marks II
Copyright © 1999 Massachusetts Institute of Technology

# Chapter 15: Generalization Prediction and Assessment

## Overview

The following sections outline some approaches to predicting and estimating generalization ability, either a priori from static parameters such as network size, or after observing training performance. The problem of estimating the true performance of a prediction system trained on a limited data set is a basic statistics problem so it is not surprising that many of these methods are direct applications of statistical techniques. Techniques mentioned here are covered in more depth in [44], [389], [317].