Martin, I should have tried before the last post to save postings, but on my machine I tried samples = 1224, species = 962, clusters = 10 with no problems at all.
> summary(test) Classification tree: tree(formula = factor(opt.10$clustering) ~ pa) Variables actually used in tree construction: [1] "pa.PICENG" "pa.ARTTSV" "pa.PSEMEN" "pa.AGRSPI" "pa.DESCES" "pa.ABILAS" [7] "pa.FESIDA" "pa.POLBIS" "pa.CAREXX" "pa.PINCON" "pa.GEUMAC" Number of terminal nodes: 16 Residual mean deviance: 1.551 = 1873 / 1208 Misclassification error rate: 0.2435 = 298 / 1224 You may want to reclassify to fewer than 50 locations, but I think it should work. Good luck, Dave Roberts Martin Wegmann wrote: > On Friday 23 September 2005 17:08, Dave Roberts wrote: > >>Martin, >> >> If the data are actually coded 0/1, the tree function would >>probably intepret them as integers and try a regression instead of a >>classification. If the dependent variable is called "var", try > > > thanks, but I think I provided too less informations. > My dependent variable are the locations which are names (I could transform > them to numbers from 1 - n). The independent variables consist of 0/1 data > (species). > If I do > tree(locations~factor(species1)+factor(species2)+.....+factor(speciesn), > sp_data) > I receive the same results as without the factor() part. > BTW just a subset of the locations are displayed what is pretty weird > considering that I included all locations in the analysis. > > Martin > > > >>x <- tree(factor(var)~species) >> >>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ >>David W. Roberts office 406-994-4548 >>Professor and Head FAX 406-994-3190 >>Department of Ecology email [EMAIL PROTECTED] >>Montana State University >>Bozeman, MT 59717-3460 >> >>Martin Wegmann wrote: >> >>>Dear R-user, >>> >>>I tried to generate classification / regression tree with a >>>absence/presence matrix of species (400) in different locations (50) to >>>visualise species which are important for splitting up two locations. >>>Rpart and tree did not work for more than 10 species which is logical due >>>to the limited amount of locations (n=50). However the error prompt is a >>>"+" and no specific message, but I am pretty sure that I did not enter a >>>false sign by mistake. >>>Is it allowed at all to use 0/1 data for this statistical technique and >>>if yes is there a way or different method to use all 400 species entries? >>>Otherwise I would apply a PCA beforehand but I would prefer to have the >>>raw species informations. >>> >>>using R 2.1.1-1 (debian repos.) >>> >>>regards, Martin >> >>______________________________________________ >>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 > > -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ David W. Roberts office 406-994-4548 Professor and Head FAX 406-994-3190 Department of Ecology email [EMAIL PROTECTED] Montana State University Bozeman, MT 59717-3460 ______________________________________________ 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