• (A) can be applied to every classification algorithm
• (B) is commonly used for dimensionality reduction
• (C) changes ridge regression so we solve a d ?? d linear system instead of an n ?? n system, given n sample points with d features
• (D) exploits the fact that in many learning algorithms, the weights can be written as a linear combination of input points