[R] problems with large data II

Spencer Graves spencer.graves at pdf.com
Fri Jan 9 15:58:56 CET 2004

      If you can't get more memory, you could read portions of the file 
using "scan(..., skip = ..., nlines = ...)" and then compress the data 
somehow to reduce the size of the object you pass to "randomForest".  
You could run "scan" like this in a loop each time processing, e.g., 10% 
of the data file. 

      Alternatively, you could pass each portion to "randomForest" and 
compare the results from several calls to "randomForest".  This would 
produce a type of cross validation, which might be a wise thing to do, 

      hope this helps. 
      spencer graves

PaTa PaTaS wrote:

>Thank you all for your help. The problem is not only with reading the data (5000 cases times 2000 integer variables, imported either from SPSS or TXT file) into my R 1.8.0 but also with the procedure I would like to use = "randomForest" from library "randomForest". It is not possible to run it with such a data set (because of the insuficient memory exception). Moreover, my data has factors with more than 32 classes, which causes another error.
>Could you suggest any solution for my problem? Thank you a lot. 
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