Hi, I am wondering why the standard deviation of the accuracy estimate is multiplied by 2 in the example on http://scikit-learn.org/stable/modules/cross_validation.html; it would be nice if someone could explain it to me.
The relevant excerpt from the page linked above: >>> clf = svm.SVC(kernel='linear', C=1) >>> scores = cross_validation.cross_val_score( ... clf, iris.data, iris.target, cv=5) ... >>> scores array([ 0.96..., 1. ..., 0.96..., 0.96..., 1. ]) The mean score and the standard deviation of the score estimate are hence given by: >>> >>> print("Accuracy: %0.2f (+/- %0.2f)" % (scores.mean(), scores.std() * 2)) Accuracy: 0.98 (+/- 0.03) Best, Sebastian ------------------------------------------------------------------------------ Dive into the World of Parallel Programming. The Go Parallel Website, sponsored by Intel and developed in partnership with Slashdot Media, is your hub for all things parallel software development, from weekly thought leadership blogs to news, videos, case studies, tutorials and more. Take a look and join the conversation now. http://goparallel.sourceforge.net/ _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general