C++ Neural Networks and Fuzzy Logic: Preface

Preprocessing Data

We now begin the preprocessing effort. As mentioned before, this will likely be where you, the neural

network designer, will spend most of your time.

A View of the Raw Data

Let’s look at the raw data for the problem we want to solve. There are a couple of ways we can start

preprocessing the data to reduce the number of inputs and enhance the variability of the data:

•  Use Advances/Declines ratio instead of each value separately.

•  Use New Highs/New Lows ratio instead of each value separately.

We are left with the following indicators: