Hi I am developing a fraud prediction model. Because this is a highly unbalanced classification problem I have chosen to try to resolve it by Random Forests.
Inspired by this article
I have chosen to try Balanced Random Forests.
For now I am not sure how to implement these Forests in R.
The article suggests that: For each iteration in random forest, draw a bootstrap sample from the minority class.
Randomly draw the same number of cases, with replacement, from the majority class.
Is this achieved by specifying these parameters?
replace = TRUE strata = fraud.variable sampsize = c(x,x) where x is the size of samples to be drawn