Previous chapters have formulated learning problems within a frequentist framework. Frequentist learning aims to determine a value of the model parameter θ that approximately minimizes the population loss. Since the population loss is not known, this is in practice done by minimizing an estimate of the population loss Lp(θ) based on training data – the training loss L𝒟(θ).
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