View Single Post
Old 06-20-2015, 05:31 AM
yaser's Avatar
yaser yaser is offline
Join Date: Aug 2009
Location: Pasadena, California, USA
Posts: 1,478
Default Re: Bias-Variance Analysis

Originally Posted by prithagupta.nsit View Post
How to generalize noise and during the calculation of bias and variance, how can we ignore the error e in the target function?

How to determine the predictions and prediction errors for different values of x?
The formula for decomposing the out-of-sample error into bias+variance+noise is discussed in Lecture 11 of the Learning From Data online course, in the part corresponding to slides 18-20.

If you look at this derivation, what you refer to as the error in the target function (which I assume is the noisy part) is not ignored. Also, the formula is given for each value of \bf x.

Of course, evaluating these terms explicitly requires knowledge of f, which is the case in bias-variance analysis in general. You can calculate them in your example since you spelled out the target. The benefit is to illustrate how these quantities change as you vary the number of data points, the level of noise, etc.
Where everyone thinks alike, no one thinks very much
Reply With Quote