Question: a Machine Learning algorithm uses a finite hypothesis classH .h M) with M 1024 to select a hypothesis g e H with the smallest training

a Machine Learning algorithm uses a finite hypothesis classH .h M) with M 1024 to select a hypothesis g e H with the smallest training error LD (g) among all hypotheses in H. Let L() be the true risk of g. Give the smallest number of data points N required to ensure that with probability at least 0.99 we have 14 (g)-LD(g)| 0.05

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