Hi Alain, thanks for the fast response. I've the same results with iris data, but when I use my data (mentioned in the first message), I have different results.
Regards, Alejo 2009/10/14 Alain Guillet <alain.guil...@uclouvain.be> > Hi, > > I did it with > > Iris <- data.frame(rbind(iris3[,,1], iris3[,,2], iris3[,,3]), Sp = > rep(c("s","c","v"), rep(50,3))) > train <- sample(1:150, 75) table(Iris$Sp[train]) > z <- lda(Sp ~ ., Iris, prior = c(1,1,1)/3, subset = train) > > Then I did plot(z,xlim=c(-10,10),ylim=c(-10,10)) before drawing > points(predict(z)$x, > col=palette()[predict(z)$class],xlim=c(-10,10),ylim=c(-10,10)) and all the > points are superimposed. The only difference I found was the different x- > and y-axis when I drew them separately, i.e. > plot(z) > plot(predict(z)$x, col=palette()[predict(z)$class]) > > > Alain > > > > Alejo C.S. wrote: > >> I'm confused on how is the right way to plot a discriminant analysis made >> by >> lda function (MASS package). >> (I had attached my data fro reproduction). When I plot a lda object : >> >> X <- read.table("data", header=T) >> >> lda_analysis <- lda(formula(X), data=X) >> >> plot(lda_analysis) >> >> #the above plot is completely different to: >> >> plot(predict(lda_analysis)$x, col=palette()[predict(lda_analysis)$class]) >> >> that should be the same graph than the first? >> >> In the second case, I use predict function to obtain the LD1 and LD2 >> coordinates of lda_analysis (predict(lda_analysis)$x) and it's respective >> class (predict(lda_analysis)$class), but it seems that the classes are >> different: >> >> table(X$G3, predict(lda_analysis)$class) >> >> B G M >> B 29 0 3 >> G 0 26 2 >> M 4 0 46 >> >> >> any clues? >> Regards, >> ------------------------------------------------------------------------ >> >> ______________________________________________ >> 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. >> >> > > -- > Alain Guillet > Statistician and Computer Scientist > > SMCS - Institut de statistique - Université catholique de Louvain > Bureau c.316 > Voie du Roman Pays, 20 > B-1348 Louvain-la-Neuve > Belgium > > tel: +32 10 47 30 50 > > [[alternative HTML version deleted]]
______________________________________________ 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.