Hyperparameters for each machine learning algorithm (where applicable) which we explored during the gridsearch cross-validation. n_estimators is the number of trees, max_features is the number of features to consider when looking for the best split within a tree, min_samples_leaf is the minimum number of objects required to be at a leaf node, criterion is the function that measures the quality of the split, min_samples_split is the minimum number of samples required to make a split, max_depth limits the maximum depth of the trees, and learning_rate (used only in the boosted model building methods of ADA and GBT) shrinks the contribution of each classifier by the set value.