To clarify your point, we need to distinguish between pruning dimensions and projecting onto a k < N set of new orthogonal dimensions. The name of PCA does make it sound like you are selecting dimensions.
> The name of PCA does make it sound like you are selecting dimensions.
I certainly thought that!
Using somes terms from the previous comment, does this mean that the k < N subspace is not (necessarily) a subset of the N-space? Or is the subspace a subset of the data with a different coordinate system?
(Yes, I'm still trying to intuitively grasp these ideas.)
I certainly thought that!
Using somes terms from the previous comment, does this mean that the k < N subspace is not (necessarily) a subset of the N-space? Or is the subspace a subset of the data with a different coordinate system?
(Yes, I'm still trying to intuitively grasp these ideas.)