Normalize coef by default

[jnothman]

The predictions of a linear model are invariant to the scale of its weights. Thus the scale of weights are determined by regularisation (and, I think, the bias term if unregularised). Are weights therefore more comparable across competing linear models if scaled by default (e.g. to unit vector)?

[kmike]

Coefficient scale affects probability output - if coefficients are large then classifier is more "confident" - probabilities are closer to 0 and 1, at least for logistic regression.

Currently we're normalizing coefficients when computing colors in show_weights / show_prediction, so currently looking at the colors is a way to compare two models with different coefficient scale.

I can see how normalizing coefficients to unit scale (and showing this scale) can be helpful. But it also can be more confusing - what user see is no longer vanilla coefficients.