On Mon, Feb 27, 2017 at 10:13:04PM +0000, Ludovico Coletta wrote: > The data is stored in a numpy array (shape: 68, 24). We are using scikit 18.1
> I saw that I wrote something wrong in previous email. Your solution is indeed > correct if we leave Scikit decide how to manage the inner loop. This is what > we > did at the beginning. By doing so, we noticed that the classifier's perfomance > decrease (in comparison to a non-optimised classifier). With 68 samples, it is not that surprising the model-selection with cross-validation is not able to select a good model. We found the same problem in brain imaging data [1], and it's an intrinsic problem due to small sample sizes: cross-validation is just not very accurate in these settings. Gaël [1] https://arxiv.org/abs/1606.05201 _______________________________________________ scikit-learn mailing list [email protected] https://mail.python.org/mailman/listinfo/scikit-learn
