As seen in the preceding chapter, when a reliable model p(x,t) is available to describe the probabilistic relationship between input variable x and target variable t, one is faced with a model-based prediction problem, also known as inference. Inference can in principle be optimally addressed by evaluating functions of the posterior distribution p(t|x)=p(x,t)/p(x) of the output t given the input x.
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