Please provide the information the posting guide asks (version of R, packages used, version of package used, etc). There are no yaImpute() or yai() functions in the randomForest package. Andy
________________________________ From: [EMAIL PROTECTED] on behalf of Ricky Jacob Sent: Wed 4/11/2007 5:55 AM To: r-help@stat.math.ethz.ch Subject: [R] Random Forest Imputations [Broadcast] Dear All, I am not able to run the random forest with my dataset.. X<- 280 records with satellite data(28 columns) - B1min, b1max, b1std etc.. y<- 280 records with 3 columns - TotBasal Area, Stem density and Volume yref <- y[1:230,] #Keeping 1st 230 records as reference records want to set 0 to y values for records 231 to 280.. yimp <- y[231:280,] #records for which we want to impute the basal area, stem density and volume mal1 <- yai(x=x, y=yref, method="mahalanobis", k=1, noRefs = TRUE) # This works fine for mahalanobis, msn, gnn, raw and Euclidean Want to do a similar thing with random forest where the 1st 230 records alone should be used for calculating Nearest Neighbours for the records with number 231 to 280.. What needs to be done.. Went through the yaImpute document.. but all i could do without any error message was to have NN generated using the yai() where all 280 records have been used for finding nearest neighbour. Regards Ricky [[alternative HTML version deleted]] ______________________________________________ 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 and provide commented, minimal, self-contained, reproducible code. ------------------------------------------------------------------------------ Notice: This e-mail message, together with any attachments,...{{dropped}} ______________________________________________ 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 and provide commented, minimal, self-contained, reproducible code.