This is sort of the “hello world” of Monte Carlo. A random forest, on the other hand, bootstraps the data (that is, samples with replacement), and grows each tree in a greedy fashion, choosing at each split from a random subset of the variables the one that most reduces the “node impurity” - be that measured via Gini or information gain or the MSE. read more
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. read more