Which of the statements about the components of a classification tree are true? Tick all that apply. If a categorical predictor used in a classification tree has 5 levels, it is NOT possible that a parent node could be split into 5 child nodes in a single step. A particular node in a classification tree can only be a parent node OR a child node (but not both). A classification tree can only have one root node, no matter how many candidate predictors there are. O If we build a tree based on a sample of 500 observations, and run these same observations through the fitted tree, it is possible that one of the nodes ends up "empty" (i.e. none of the observations ends up in a given nodes)