This stack exchange post - https://stats.stackexchange.com/questions/80507/what-is-a-gaussian-discriminant-analysis-gda - discusses GDA, a machine learning method for classification. I would like to implement something like this analysis in R.
I've seen posts for discriminant analysis in R using linear and quadratic discriminant analysis (http://rstudio-pubs-static.s3.amazonaws.com/35817_2552e05f1d4e4db8ba87b334101a43da.html) but nothing for GDA?
I guess my questions are, because I'm not 100% familiar with these methods, (1) whether GDA is different from or a subset of LDA and QDA, and if there is an R package / functions for GDA in R like there are for LDA and QDA (the lda() and qda() functions in the MASS package). Maybe I should be asking if I actually want to be performing GDA with my data (I'm not actually sure if the joint distribution of the features follow a gaussian dist), or if lda or qda may be better?