Error coming while using Random Forest using R

Question

I am using a dataset containing mvar_1 as column, having names of one of 5 parties that citizen voted for last year. Other variables are just demographic variables, as the number of rallies attended for each parties, other stuffs.

When I use the following code:

data.model.rf = randomForest(mvar_1 ~ mvar_2 + mvar_3 + mvar_4 + mvar_5 + 
                             mvar_6 + mvar_7 + mvar_8 + mvar_9 + mvar_10 + 
                             mvar_11 + mvar_15 + mvar_17 + mvar_18 + mvar_21 + 
                             mvar_22 + mvar_23 + mvar_24 + mvar_25 + mvar_26 +
                             mvar_28, data=data.train, ntree=20000, mtry=15, 
                             importance=TRUE, na.action = na.omit )

This error message appears:

Error in randomForest.default(m, y, ...) : 
  Can not handle categorical predictors with more than 53 categories.

Answer 1

One of your mvar is a factor with more than 53 levels.

You may have a categorical variable with lots of levels, like demographic group, and you should aggregate it into less levels to use this package. (See here for the best way of doing it)

More likely, you have a non-categorical variable incorrectly typed as a factor. In this case you should fix it by typing your variable correctly. E.g. to get a numeric from a factor, you call as.numeric(as.character(myfactor)).

If you don't know what a factor is, the second option is probably it. You should do a summary of data.train, this will help you see which mvar are incorrectly typed. If the mvar is typed as numeric, you will see min, max, mean, median, etc. If a numeric variable is incorrectly typed as a factor, you will not see that but you will see the number of occurence of each level.

In any case, calling summary will help you because it shows the number of levels for each factor. The variables with >53 levels are causing the issue.