I think I understand how the fundamentals of bootstrapping work, but I'm not sure I understand how I can use bootstrapping for model selection or to avoid overfitting.
For model selection, for example, would you just choose the model that yields the lowest error (maybe variance?) across its bootstrap samples?
Are there any texts that discuss how to use bootstrapping for model selection or validation?
EDIT: See this thread, and the answer by @mark999 for more context behind this question.