On Fri, Nov 30, 2012 at 01:58:48PM +0100, Philipp Singer wrote: > > Don't. This is not a good model selection strategy, and it is very > > costly. Use a stratified kfold with k between 5 or 10.
> Well, I only have a few samples and I am explicitely interested in > seeing the performance of each sample alone trained on the rest. Still. I keep having this discussion with users: leave one out is about the worst strategy possible because it is the one with the largest variance on the test accuracy estimation. You'll have to believe me on this, because I don't have time to dig up the relevent papers (there is a bit of literature on this, but it's really hard to find, and it's more folk knowledge in machine learning. G ------------------------------------------------------------------------------ Keep yourself connected to Go Parallel: TUNE You got it built. Now make it sing. Tune shows you how. http://goparallel.sourceforge.net _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
