While growing random forest, which kind of trees are used? CART, C4.5 or C5.0 etc. or all of them? So i mean, when we grow random forest, we produce hundreds even thousands of trees, and these trees are produced based on which approach (CART, C4.5, C5.0).

  • 1
    $\begingroup$ It depends on the implementation of random forest you are using $\endgroup$
    – Simone
    Oct 17, 2016 at 13:04
  • 2
    $\begingroup$ The randomForest() function of randomForest package uses CART. $\endgroup$
    – Lella
    Oct 17, 2016 at 13:15
  • $\begingroup$ A more interesting question would be, does the type of trees matter in the overall performance of RF. If yes, which type of construct is better. $\endgroup$
    – horaceT
    Oct 18, 2016 at 2:57

2 Answers 2


"which kind of trees are used?"

This depends on implementation. Generally, any bootstrap-aggregated attribute-bagged learner based on trees (any of them) is called Random Forest. You get different flavors using different trees.

"CART, C4.5 or C5.0 etc. or all of them?"

Any of those can be used to grow a forest. On the last point, though ("all of them"), I can't see how much useful it would be. The point of Random Forests is aggregating nearly random generalizations to build a strongly informative one, and I don't think using different tree algorithms would improve this aspect of forests much.

  • $\begingroup$ Actually, i use R for the building random forest "randomForest" function and i use the results in my thesis for that reason i need to explain which tress are used. when i do some researches, generally i saw CART is used for the randomForest in R. But i am not sure about that. $\endgroup$ Oct 19, 2016 at 21:40

Function randomForest() in R uses CART algorithm. However, any of them might be used.


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