Hi, I'm not a programmer, so I have a question about R functions, I run the Random Forest regression models, but I would like to run the random forest model 1000 times with different random sample set. to check the uncertainty of the regression model estimates.
exemple of data: ################################# table= all Y: all$AGB X variables: Variables=as.matrix(all[, c( "min", "max", "avg", "qav", "std", "ske", "kur", "p50", "d50", "d06", "d07", "d08", "dns_gap")]) rf.Model=randomForest(Variables, all$AGB, importance=T) ################################# Can I use Monte Carlo method or Bootstrap to simulate 1000 different sample set and Run 1000 x times the Random Forest regression? But How can I do that? Could somebody have an idea with the script? Thanks! Fran [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.