Random Forest - Predict using less estimators
Once trained, you can access these via the "estimators_" attribute of the random forest object.
I've trained a Random Forest (regressor in this case) model using scikit learn (python), and I'would like to plot the error rate on a validation set based on the numeber of estimators used. In other words, there's a way to predict using only a portion of the estimators in your RandomForestRegressor?
Using predict(X) will give you the predictions based on the mean of every single tree results. There is a way to limit the usage of the trees? Or eventually, get each single output for each single tree in the forest?