exploits the fact that in many learning algorithms, the weights can be written as a linear combination of input points

can be applied to every classification algorithm

is commonly used for dimensionality reduction

changes ridge regression so we solve a d ?? d linear system instead of an n ?? n system, given n sample points with d features

exploits the fact that in many learning algorithms, the weights can be written as a linear combination of input points

Mr. Dubey • 100.69K Points
Coach

Q. The kernel trick

(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