Model selection and evaluation involves choosing the best model to use for a given task, and determining how well that model is likely to perform on new, unseen data.
Model selection and evaluation involves choosing the model with the highest accuracy.
Model selection and evaluation involves choosing the model that performs well on the training set.
Model selection and evaluation involves choosing the most complex model available.
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