I have never used Random Forests, but I have read some about it. Until now I have used GLM/GAMLSS extensively.
I would like to know:
- What are the advantages that RF provides over GLM/GAMLSS?
- What are the disadvantages of using Random Forests?
I am starting this new study which has around 25 predictor variables, and I was wondering if I should check random forests.
One disadvantage that I could find: Random Forests, at least the popular applications, are non-updatable. Is this True? This is important for me as I will run this on some real-time data and would need to assimilate new information.