[legerdemain]

Skimming the sections on linear models, I was surprised not to see a discussion of model fit, beyond just plotting predicted values against observed ones. Basic predictive models like linear and logistic regression are simple to construct mechanically. It's a substantially more involved task to quantify their degree of fit and, better yet, prove that the methods are optimal and unbiased (in a statistical sense).

[dafrdman]

I agree though I saw that as outside the scope of this book. I tried to be clear in the introduction that the book is a "user manual" of sorts that simply shows how to construct models, rather than how to decide between them, what the benefits of each are, etc. That information is certainly important but I felt it had been covered more than adequately by books like Elements of Statistical Learning