Quote:
Originally Posted by elkka
I first thought the same thing about 1. But then, where do we see ? It is the measure of difference between E_in and E_out, which can be small, and can be big depending on the experiment. Suppose you are talking about an experiment with very large numbers, like the number of minutes people use in a month on a cell phone (which, say, average 200). Than it is totally meaningful to consider a prediction that assures you that (or 5, or 10) with probability 0.95. So, it totally makes sense to rate the bounds even if they all are >1

Except that Ein and Eout are ratios. I quote from HW2: "Eout (number of outofsample points misclassiﬁed / total number of outofsample points)".
Therefore, it is quite impossible for epsilon to ever exceed 1.