dominic senn wrote: > Hello > > I try to fit a LDA and RDA model to the same data, which has two classes. > The problem now is that the training errors of the LDA model and the > training error of the RDA model with alpha=0 are not the same. In my > understanding this should be the case. Am I wrong? Can someone explain what > the reason for this difference could be?
I assume lda from MASS? If you are using rda() from package "rda", I do not know, since the help page is not very specific in telling which parameter means what (but I guess one of them should be 1). If you choose rda() from package "klaR", the help page tells you that gamma=0, lambda=1 should produce identical results to LDA. (lambda=1 means that the pooled covariance matrix is weighted with 1 while the specific covariance matrices are weigthed with 0. Uwe Ligges > Here my code: > > LDA model: > =========== > % x is a dataframe > tmp = lda(response ~ ., data=x) > tmp.hat = predict(tmp) > tab = table(x$response, tmp.hat$class) > lda.training.err = 1 - sum(tab[row(tab)==col(tab)])/sum(tab) > > RDA model: > =========== > % x is converted into a matrix without the response > % variable. This matrix is then transposed > tmp = rda(x, y, alpha=0, delta=0) > rda.training.err = tmp$error / dim(x)[2] > > % The training error provided by rda.cv() is also different > % from the training errors provided by lda() or rda() > tmp.cv = rda.cv(tmp, x=x, y=y, nfold=10) > tmp.cv$err / dim(x)[2] / 10 > > > Thanks a lot! > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > 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. ______________________________________________ R-help@stat.math.ethz.ch mailing list 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.