
#1




Variance of Eval
I'm confused about how to simplify expressions involving Var[Eval(g)].
I know that Var[Eval(g)] = E [ ( Eval(g)  E[Eval(g)] )^2] = E [ ( Eval(g)  Eout(g) )^2] and that for classification P[g(x) != y] = Eout(g). I'm not sure how to bring K into any of these expressions. Any help would be greatly appreciated. 
#2




Re: Variance of Eval
Here are two useful facts from probability:
The variance of a sum of independent terms is the sum of the variances: When you scale a random quantity its variance scales quadratically: [Hint: so, if you scale something by its variance scales by ; the validation error is the average of K independent things (What things? Why are they independent?)] Quote:
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