1) (True/False) In general, a random forest can be considered
a special case of bagging and it tends to have better out of
sample accuracy
True
False
2) Usually the first step to fit a random forest classifier model
using scikit learn is to:
import classifier ensemble from the sklearn.random forest
module
e.g. from sklearn.randomforest import ClassifierEnsemble
import random forest from the sklearn.classifierensemble
module
e.g. from sklearn.classifierensemble import RandomForest
import classifer from the sklearn.randomforest module
e.g. from sklearn.randomforest import Classifer
import random forest classifer from the sklearn.ensemble
module
e.g. from sklearn.ensemble import RandomForestClassifer
