Hello! I need some help with the linear discriminant analysis in R. I have some plant samples (divided into several groups) on which I measured a few quantitative characteristics. Now, I need to infer some classification rules usable for identifying new samples. I have used the function lda from the MASS library in a usual fashion:
lda.1 <- lda(groups~char1+char2+char3, data=xxx) I'd like to obtain the classification functions for the particular groups, with the aid of which I could classify unknown samples. I know I can use predict.lda to classify such samples, but I need to obtain some equations into which I could simply put the measured values of an unknown sample manually and the result would predict which group the sample most probably belongs to (like in eg. STATISTICA). I haven't found out how to extract these functions from the lda output. Could somebody give me some advice? Thank you in advance, Pavel Kur ______________________________________________ R-help@r-project.org 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.
