how to use classwt in randomForest of R?

Question

I have a highly imbalanced data set with target class instances in the following ratio 60000:1000:1000:50 (i.e. a total of 4 classes). I want to use randomFor

Answer 1

classwt is correctly passed on to randomForest, check this example:

library(randomForest)
rf = randomForest(Species~., data = iris, classwt = c(1E-5,1E-5,1E5))
rf

#Call:
# randomForest(formula = Species ~ ., data = iris, classwt = c(1e-05, 1e-05, 1e+05)) 
#               Type of random forest: classification
#                     Number of trees: 500
#No. of variables tried at each split: 2
#
#        OOB estimate of  error rate: 66.67%
#Confusion matrix:
#           setosa versicolor virginica class.error
#setosa          0          0        50           1
#versicolor      0          0        50           1
#virginica       0          0        50           0

Class weights are the priors on the outcomes. You need to balance them to achieve the results you want.

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On strata and sampsize this answer might be of help: https://stackoverflow.com/a/20151341/2874779

In general, sampsize with the same size for all classes seems reasonable. strata is a factor that's going to be used for stratified resampling, in your case you don't need to input anything.