About the oob score I have a question:
if i understood what jeremy said (english is not my native language) the oob score allows you not to need a validation set to see how well the model works. For this reason it is also useful when we have little data.
my question is why in notebooks jeremy uses:
m = RandomForestRegressor(n_estimators=40, n_jobs=-1, oob_score=True) m.fit(X_train, y_train) print_score(m)
If i use the oob_score shouldn’t I use m.fit with the complete data and not only with the x_train and the y_train?