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

Reply via email to