I have been doing some research on different type of machine learning (ML) algorithms such as random forest/SVM etc. in order to model and best predict pharmaceutical needs of patients suffering from a particular type of kidney autoimmune disease.
What I was hoping someone could explain to me is what are the differences in predictive ability between Monte Carlo simulations and random forest classifiers? How is their real world application different?
Any comments would be greatly appreciated.