This is an ensemble model that does not use bootstrapped samples to fit the base trees, takes residuals into account, and fits the base trees iteratively:1 pointBoostingRandom TreesBaggingRandom Forest

Random Forest has _________ as base learning models1 pointmultiple decision treesbaggingentropyNone of these

What is an ensemble model that needs you to look at out of bag error?1 pointStackingLogistic Regression.Out of Bag RegressionRandom Forest

Question 6This tree ensemble method only uses a subset of the features for each tree:1 pointStackingAdaboostBaggingRandom Forest

Which of the following machine learning algorithm is based upon the idea of bagging?(1 Point)Decision treeRandom-forestClassificationRegression

Which type of Ensemble modeling approach is NOT a special case of model averaging?1 pointBoosting methodsRandom Forest methodsThe Bagging method of Bootstrap aggregationThe Pasting method of Bootstrap aggregation