Random Forests Leave a reply Welcome to your Random Forests Part I Which of the following are hyperparameters for a random forest? (select all that apply) the number of trees in the forrest max leaf depth the type of weak classifier learning_rateWhat is 'random' about a random forest? (select all that apply) the target variable the maximum leaf depth the features considered when splitting a node the data used to train the model the number of trees createdDoes a random forest use boosting or bagging?boostingbaggingBagging is an abbreviation ofBootstrapped aggregationBackpropagation gradientBoosted aggregationBayesian aggregationBag of Words GroupingWhat is a suggested starting point for the number of variables used per step?one half the number of variablesthe square root of the number of variablesone tenth the number of observations in the datasetthe square root of the number of observations in the datasetthe square of the number of variablesHow is out-of-bag error determined?Scoring the random forest model on the observations that were not used to train the modelScoring the trees on observations that were not used in training those treesScoring the random forest model on the observations used to train the modelScoring the trees on observations that were used in training those treesPlease fill in the comment box below. Time is Up! Time's up
