In-sample error and Max Likelihood
The learning bounds we learnt in the course relate the generalization error of h, where h is the best hypothesis in terms of in-sample error, to the VC dimension.
In practice very often the best hypothesis h' is computed/estimated using Max Likelihood.
Is there a connection between the in-sample error of h' (the max likelihood hypothesis) and the minimum in-sample error possible?
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