 Following Christopher M. Bishop (2006), we may derive the bias-variance decomposition of mean squared error of h as follows. Let h refer to our estimate \(h(X)\) of Y, r refer to the true value of Y, and \(\mathbb{E}\left[ h \right]\) the expected value of the estimate h. Then, 