
#1




questions 5 & 6

#2




Re: questions 5 & 6
...or are we just supposed to use the points generated in order to calculate g_bar? That would mean that bias and var have twice as many points to average over than the number of data sets used to calculate g_bar, because each data set had two two data points.

#3




Re: questions 5 & 6
So to calculate g_bar you used 2 points to get each hypothesis and average over them.
Now Bias and var should come from the entire range of the real line. I would say about hundreds range from 1 to 1. 
#4




Re: questions 5 & 6
Are you saying generate 100 new points?

#5




Re: questions 5 & 6

#6




Re: questions 5 & 6
All these are approximating integrals.
Many problems really are sums, but this one is, theoretically, continuous. First you do 2D integrals to compute a, a 1D integral to compute bias, and a 3D integral to compute variance. (I think it would also work to compute bias+variance in the first place, and subtract bias to get variance, but I didn't try that.) I used equally space points for all, but you could also use random points. If I was in the right mood, I might have done Gaussian quadrature, or some other numerical integration method. 
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