True, but I think this is an interesting point. I had in mind the advantages of the concordance correlation coefficient for regression problems, but the Pearson correlation seems to be more relevant for a subset of problems, as Mathieu commented.
2015-09-08 15:12 GMT+01:00 Andreas Mueller <[email protected]>: > > > On 09/08/2015 06:42 AM, Mathieu Blondel wrote: > > Pearson correlation between y_true and y_pred is also a standard > > evaluation metric in genomic selection. In a sense, it can be seen as > > a ranking measure since y_true and y_pred don't need to be equal: they > > only need to be collinear to achieve perfect correlation. > > > > +1 for adding pearson_correlation_score > I thought we were discussiong the concordance correlation coefficient? > > > ------------------------------------------------------------------------------ > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >
------------------------------------------------------------------------------
_______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
