Re: [R] CART for 0/1 data

From: Dave Roberts <>
Date: Sat 24 Sep 2005 - 03:25:28 EST


     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:

>>     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
>>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
>> mailing list
>>PLEASE do read the posting guide!

David W. Roberts                                     office 406-994-4548
Professor and Head                                      FAX 406-994-3190
Department of Ecology                         email
Montana State University
Bozeman, MT 59717-3460

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Received on Sat Sep 24 03:34:55 2005

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