How many cases do you have? Since you apparently expect the dataset to be usable in R, you only have room to store a dataset with 200 cases or so (let alone space to analyse it).
Even selecting *one* variable is statistically nonsensical with less than millions of cases (as otherwise the possibility of chance agreement of predictors is too high -- and I don't known enough about your problem to do even a rough calculation with any confidence). On Fri, 2 Jul 2004, daisy wrote: > I have about half million binary features, and would like to find a > model to estimate the continous response. According to the inference, I > can express predictors and response by linear model. (ie. Design matrix: > large sparse matrix with 0/1. Response: Continous number) Since it is > not a classification problem, someone suggested me to try random forest > in R. However, in the randomForest help page, it points out "For large > data sets, especially those with large number of variables, calling > 'randomForest' via the formula interface is not advised: There may be > too much overhead in handling the formula." and I also gave a try on 300 > variables and R either gave me error message or no response. (OS: > Windows XP; R:1.9.0 ; RAM:512MB) Is there any way to implement random > forest on this big dataset? Any suggestion is welcome! Many thanks! -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
