How to scale an array of signed integers to range from 0 to 1? I'm using Brain to train a neural network on a feature set that includes both positive and negative values. But Brain requires input values between 0 and 1. What's the best way to normalize my data?
This is called unity-based normalization. If you have a vector $X$, you can obtain a normalized version of it, say $Z$, by doing:

$$Z = \frac{X - \min(X)}{\max(X) - \min(X)}$$