# How to visualize regression features?

In classification, if I take 2 features and color them according to label, I obtain a plot like this, which gives intuition about the effectiveness of my features.

How can I do a similar plot for regression? My aim is to gain (and give, in a paper or presentation) intuition about different features I use as input to a kernel ridge regression.

The only way I can think of is to take one dimension (i.e. one feature/input) and place it into a plot where x = feature, y = label. But I'm not sure if it will make sense. Maybe an ordering in x or y will make it nicer. But still not sure if this is a good idea enough to do. So I'm open to any advice :)

• Thanks! All my variables are continuous by the way. I would appreciate any comments on the axes (x = feature, y = label, or x = feature_1, y = feature_2?). And what about multiple features? Does it make sense to combine them with different colors, or should I do one plot per feature? If it's alright, I will wait for a little while before accepting to encourage other users commenting too :) Thanks again, – jeff Jun 5 '16 at 16:04