Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Bonus Chapter
Feature Space
This chapter is different from the others. We’re not coding anything.
The purpose of this chapter is to illustrate the effect activation functions have on
the feature space.
"What do you mean by 'feature space'?"
The feature space is the n-dimensional space where our features "live." In Chapter 3
we used two features for our binary classification, so the feature space there was
two-dimensional, a plane. In Chapter 4, we used 25 features, so the feature space
was 25-dimensional, a hyper-plane.
Two-Dimensional Feature Space
Let’s forget about hyper-planes (phew!), and go back to the comfy and familiar
world of two dimensions for now.
This is an entirely new dataset; it is not the image dataset
anymore!
Our new, two-dimensional, data has 2,000 points, evenly split into two classes: red
(negative) and blue (positive), which are neatly organized in two distinct parabolas,
as in the figure below.
Figure B.1 - Two-dimensional feature space
Two-Dimensional Feature Space | 331