I have implemented linear regression manually, for learning purposes, and I use the ["Auto MPG" data set](http://archive.ics.uci.edu/ml/datasets/Auto+MPG) as the toy data I'm applying it to.

It occured to me that I don't know how to test the efficiency of my model! With classification I can check the predicted class vs the actual class, but what do I do with regression?

For instance, using my model I predict 16.76 mpg for a car for which the actual value in the data set is 15.5. How do I decide whether this is a "good" or "bad" prediction?
I am thinking of using some thresholds ("if the predicted value is within the [actual-epsilon, actual+epsilon] interval => OK!"), but is this a good approach? And even if it is, how do I choose epsilon values?

I am aware of the fact that there's most likely no clear-cut answer, but any suggestion regarding the approach to take would be most helpful.