Hello R Gurus, I am perplexed by the different results I obtained when I ran code like this: set.seed(100) test1<-randomForest(BinaryY~., data=Xvars, trees=51, mtry=5, seed=200) predict(test1, newdata=cbind(NewBinaryY, NewXs), type="response")
and this code: set.seed(100) test2<-randomForest(BinaryY~., data=Xvars, trees=51, mtry=5, seed=200, xtest=NewXs, ytest=NewBinarY) The confusion matrices for the two forests I thought would be the same by virtue of the same seed settings, but they differ as do the predicted values as well as the votes. At first I thought it was just the way ties were broken, so I changed the number of trees to an odd number so there are no ties anymore. Can anyone shed light on what I am hoping is a simple oversight? I just can't figure out why the results of the predictions from these two forests applied to the NewBinaryYs and NewX data sets would not be the same. Thanks for any hints and help. Sincerely, Trent Buskirk -- View this message in context: http://r.789695.n4.nabble.com/Different-results-from-random-Forest-with-test-option-and-using-predict-function-tp4651970.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org 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.