Hi, I am trying to model a dataset with the response variable Y, which has 6 levels { Great, Greater, Greatest, Weak, Weaker, Weakest}, and predictor variables X, with continuous and factor variables using random forests in R. The variable Y acts like an ordinal variable, but I recoded it as factor variable.
I ran a simulation and got OOB estimate of error rate 60%. I validated against some external datasets and got about 59% misclassification error. I would like to tinker with classwt option in the function randomForest to see if I can get a better performance the model. My confusion arises from how to define these weights. If I say, classwt = c(3,6,9,1,2,3), how exactly the levels get weighted. If this is a 6X6 matrix, I can put a number in each cell to adjust the weights. How does classwt option work? Thank you in advance for any ideas. Nagu ______________________________________________ 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.