I am working with a dataset of 17 predictors and 1000 observations. I am trying to find the most important variables, for which I am using the permutation-based OOB-MSE.
My problem is that each time I run the random forest, the two most important variables remains invariable but the ranking of other less important variables changes, even keeping the command with the same amount of
mtry. Further, I have also noticed that the mean of squared residuals and the % of variance explained also change, not too much, they keep within the range 41.5-43.3% but they change.
I have read that in Random Forest results can change slightly, so maybe this could be normal. However, I am trying to optimize my model using the
tuneRF(x=datos[,c(9,15,18,20,27,32,38,40,70,73,95,123,131,132,133,134)], y=datos.fin3$dnbr, ntreeTry = 500, stepFactor=2, improve=0.05, trace=TRUE, plot=TRUE, dobest=FALSE)
and each time a run the function the optimized
mtry also changes. Could someone tell me if this is normal?