Quote:
Originally Posted by ilya239
Thanks for the explanation.
In HW4 #4 the average hypothesis is measurably shifted from the hypothesis set member giving the lowest mean squared error. Probably because two-point dataset is too small, i.e. this is not representative of realistic cases?
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Well, it is also that the two point data set is small relative to the two parameter hypotheses. If you have 100 points, and 99th degree polynomials, it would also have large variance. I will guess that minimizing bias plus variance happens with the number of fit parameters near the square root of the number of points per data set.