random_state in random forest
train_test_split splits arrays or matrices into random train and test subsets. That means that everytime you run it without specifying random_state, you will get a different result, this is expected behavior.
When you use random_state=any_value then your code will show exactly same behaviour when you run your code.
I just learned how to use the machine learning model Random Forest; however, although I read about the random_state parameter, I couldn't understand what it does. For example, what is the difference between random_state = 0   and   random_state = 300
Can someone please explain?