This question explores random forest classifiers by using scikit$-$learns ensemble.RandomForestClassifier. You will make two plots and answer questions about them.$($a$)$For the first plot, use a ensemble.RandomForestClassifier and the best depth you found $2($b$)$ii as max$\_$depth. We will now find the optimal setting of a second parameter, n estimators. Vary the number of trees in the forest via the parameter n$\_$estimators and plot its $10-$fold cross$-$validated accuracy $($use n$\_$estimators $=1,2,...,20).$ Again, use $10$ as your random seed for your classifier and cross$-$validation.