Why do we use PCA?
- Objective and hierarchical identification of most characteristic features.
- Features are independent and uninformed.
PCA is an orthogonal coordinate system transformation that prioritizes maximum variance.
Here what that statement looks like in 2D.
The following is a 3D example showing the same effect in a different sense.