... and even more generally, is generally misleading. ;-) (search "problems with R^2" or similar for why).
Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed, Jan 8, 2020 at 9:37 AM Norm Matloff <nsmatl...@ucdavis.edu> wrote: > Glad to hear it now works for you. But speaking more generally, note that > R-squared is the squared correlation between the predicted Y and actual Y > values. E.g. > > lmout <- lm(y ~ x) > print(cor(lmout$fitted.values,y)^2) > > One can use this in any regression setting, even machine learning methods. > > Norm > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
