Dear Bioconductor community,
i have some gene expression microarray data, on which i would like to fit a machine learning methodology and construct a classifier regarding a binary outcome(Disease status). Although from literature and various papers i have found various packages and methodologies in R, as i would like also to add additional continuous variables alongside the genes, to train my classifier. Thus, as i dont have experience in this specific topic: is this approach generally appropriate for any model in classification procedures(i.e. randorm forests, SVM etc) ? or it is restricted to specific methodologies/packages in R that can handle this possibility ? I have knowledge of the caret R package which implements various methodologies, but my main concern is particularly about the "validity" of this "multivariate" approach !!
Any ideas or suggestions would be grateful !!