FeatureEffects vs. categorical features

[Mark-iGit]

I have an issue with FeatureEffects and my data when categorical features are present but I cannot find a hint in the documentation that categorical features would need a special treatment. It's probably me being stupid but when trying to reproduce the issue with the code and data from the documentation I do get a different error yet it won't run so I'm wondering if there might be a general issue with categorical features?

When adding a random categorical feature to the Boston data set from the example in the documentation of FeatureEffects the code throws an error:

Error in UseMethod("droplevels") : no applicable method for 'droplevels' applied to an object of class "character"

Here's the modified code:

library("rpart")
library("iml")

data("Boston", package = "MASS")

# Adding a random categorical feature
Boston$cat <- sample(letters[1:2], nrow(Boston), replace = T) # w/o this line of code it works

rf <- rpart(medv ~ ., data = Boston)
mod <- Predictor$new(rf, data = Boston)
eff <- FeatureEffects$new(mod)

[Mark-iGit]

Sorry, just realized it has to be a factor... which it is in my dataset that's why the error is different. So probably something with my data... never mind