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Model selection refers to choose the best statistical machine learning model for a particular problem. For this task we need to compare the relative performance between models. Therefore the loss function and the metric that represent it, becomes fundamental for selecting the right and non-overfitted model.
We can state a machine learning supervised problem with the following equation: