So what about asking your teacher (who seems to be Peter Filzmoser) and try to find out your homework yourself? You might want to think about some assumptions that must hold for LDA and look at the class of your explaining variables ...
Uwe Ligges Soare Marcian-Alin wrote: > Hello, > > I want to make a linear discriminant analysis for the dataset olive, and I > get always this error:# > Warning message: > variables are collinear in: lda.default(x, grouping, ...) > > ## Loading Data > library(MASS) > olive <- url(" > http://www.statistik.tuwien.ac.at/public/filz/students/multi/ss07/olive.R") > print(load(olive)) > > y <- 1:572 > x <- sample(y) > y1 <- x[1:286] > > train <- olive[y1,-11] > test <- olive[-y1,-11] > > summary(train) > summary(test) > > table(train$Region) > table(test$Region) > > # Linear Discriminant Analysis > z <- lda(Region ~ . , train) > predict(z, train) > > z <- lda(Region ~ . , test) > predict(z, test) > > Thanks in advance! > > > > ------------------------------------------------------------------------ > > ______________________________________________ > 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.