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) learning_rate max leaf depth the type of weak classifier the number of trees in the forrestBagging is an abbreviation ofBoosted aggregationBackpropagation gradientBayesian aggregationBag of Words GroupingBootstrapped aggregationWhat is 'random' about a random forest? (select all that apply) the number of trees created the target variable the maximum leaf depth the data used to train the model the features considered when splitting a nodeHow is out-of-bag error determined?Scoring the random forest model on the observations used to train the modelScoring the random forest model on the observations that were not used to train the modelScoring the trees on observations that were used in training those treesScoring the trees on observations that were not used in training those treesDoes a random forest use boosting or bagging?baggingboostingWhat is a suggested starting point for the number of variables used per step?the square root of the number of observations in the datasetthe square root of the number of variablesone half the number of variablesthe square of the number of variablesone tenth the number of observations in the datasetPlease fill in the comment box below. Time is Up! Time's up
