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#1
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I computed E_cv for part (d) in HW9. I compared the theoretical and estimated results and verfied they are same for all values of lambda. However, when I plot E_test(w_reg(lambda)) vs lambda against E_cv vs lambda, I observe E_test to be always larger than E_cv. I think it should not be the case because E_test is approximately E_out and E_out should be always less than E_cv.
I was wondering if I am making a mistake somewhere. I checked code etc. but cannot think of anyway to do some type of sanity check anywhere. Is there any way to know where the problem might be? |
#2
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Ecv is an estimate for Eout based on N-1 points. So you expect Eout<Ecv because Eout is based on learning from N points. However, Etest is just an estimate for Eout and can be higher or lower, though unbiased.
Also note that if there is data snooping, that is if the test set in [i]any[i] way affected the learning process that produces ![]() Quote:
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#3
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Hi Professor, for the 7th problem in HW9 the Ecv and Etest are classification error or regression error? Thanks!
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#4
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The digits problem is about classification, so all errors are classification errors.
However, one can us different algorithms to get your final classifier, one being the regression algorithm treating the ![]()
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Have faith in probability |
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