Hi everybody. Me again. I was getting some unexpected behaviour from the error metrics. Consider the following:
import numpy as np from sklearn.datasets import load_digits from sklearn.metrics import zero_one_score zero_one_score(digits.target, np.vstack(digits.target)) >>> 0.10 The shape of digits.target is (1797,), the shape of the stacked version is (1797, 1). That seems to cause broadcasting in "==". I thought utils.check_arrays was meant to avoid such problems, but it does not change the shape of these two arrays. What did I do wrong or what did I misunderstand here? Obviously I could reshape either array so that no broadcasting happens. I feel the problem is somewhat subtle, though, and it took me 3 hours to find. If you feel that is a problem, should it be addressed in "check_arrays"? Cheers, Andy ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-novd2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
