Let's say that I have to chose the best model to predict a variable but my sample size is small. I would like to resample my data using the bootstrap, run each model and evaluate its prediction error with cross validation on each bootstrap sample. In the end I will chose the model with the lowest average prediction error.
Is this a acceptable procedure? If yes is there something I should be aware of while using this procedure?