1 ⋯ = = =1 ( ) Estimated by using MSE Φ, = ( ) : design matrix = ΦΦ −1Φ Linear Regression ( basis function (⋅) have to be given) Gaussian Process Regression ( Kernel function have to be given) We introduce prior distribution ~N , λ2 = follows gaussian distribution ~ , λ2 ≡ , (∗|∗, )~ ∗ T−1, ∗∗ − ∗ T−1∗ ∗ ~N , ∗ ∗ T k∗∗ ∗ = ∗, 1 , ⋯ , (∗, ) k∗∗ = ∗, ∗ ,′ = λ ′ = 1 exp − 1 2 − ′ 2 Example: RBF Kernel