I Have a dataset which contains various categorical variables and no numeric variable. I converted the variables to ordered factors by:
df$colA= factor(df$colA,levels=unique(df$colA), ordered=TRUE)
Now I am making a random forest model and then making a tree using below code:
getTree(model.rf, 1, labelVar=TRUE) #model.rf is the model created using df and various columns
I get the tree something like below:
left daughter right daughter split var split point status prediction 1 2 3 colA 1.5 1 <NA> 2 4 5 colB 2.5 1 <NA>
and so on....
Both my split var are ordered factor categorical variables. Now how do I interpret split point as 1.5 or 2.5. I can't say the split is between two groups.
To explain it further: Lets say
ColA is Gender with levels as
Weight with levels as
Now to explain it to stakeholders I can't say when the gender is between Male and Female and the Weight is between Medium to High.. the probability of happening something is high.
Can someone help me in how to explain RF tree when dealing with categorical variable?