The "ctree" package implements conditional inference trees. What is the distinguishing aspect of a cforest solution compared to a randomForest solution?
A) Conditional inference trees use partial correlations as splitting criteria.
B) Conditional inference trees use factor analysis to form clusters.
C) Conditional inference trees use p values from significance tests as splitting criteria
D) Conditional inference trees do not incorporate a random element.

Question

Quizplus · Accepted Answer

The distinguishing aspect of a cforest solution compared to a randomForest solution is that conditional inference trees in the cforest package use p values from significance tests as splitting criteria, whereas randomForest does not incorporate p values into the splitting criterion.

The "Ctree" Package Implements Conditional Inference Trees