I have a random forest being applied to 7 different input variables to predict a particular classification. I've done a grid search on the hyperparameters
ntree and it seems as though the algorithm is most accurate when
mtry is at 6 (the highest value for
mtry I allowed as a hypothetical value in my search). This finding has also been confirmed when applied to a test set. I have an intuition that
mtry should always be less than the number of total variables in the model but I can't find anything that explicitly states this.
My question Is there an upper limit to
mtry as I think there should be? And if indeed that's the case, what would it indicate if my model gets more accurate as I approach that upper limit? Is that something to be concerned about?