Due to recent updates, all users are required to create an Altair One account to login to the RapidMiner community. Click the Register button to create your account using the same email that you have previously used to login to the RapidMiner community. This will ensure that any previously created content will be synced to your Altair One account. Once you login, you will be asked to provide a username that identifies you to other Community users. Email us at Community with questions.
Decision Tree Operator - C5 or C4.5 algorithm?
Hello experts,
does RM still uses the C4.5 algorithm for his decision tree operator? I found some really old topics that say it uses the C4.5 algorithm.
Kind regards,
Christopher
Tagged:
0
Best Answer
-
MartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,527 RM Data Scientist
The shipped descion tree is actually a own implemtation. I am not sure if it follows any direct implementation, i think it is some mixture, but I am not sure.
If you want to have C4.5 you may have a look on W-J48.
~Martin
Edit: Just looked it up:
* <p>
* This operator learns decision trees from both nominal and numerical data. Decision trees are
* powerful classification methods which often can also easily be understood. This decision tree
* learner works similar to Quinlan's C4.5 or CART.
* </p>
*
* <p>
* The actual type of the tree is determined by the criterion, e.g. using gain_ratio or Gini for
* CART / C4.5.
* </p>- Sr. Director Data Solutions, Altair RapidMiner -
Dortmund, Germany0
Answers
Hi Martin,
thank your very much for your help! But where did you found the information? Is it from a public source which I dond know? I can not find the information in operators manual.
Kind regards,
Christopher
Dear Christopher,
i copied it from the source code. It is available at https://github.com/rapidminer/rapidminer-studio/blob/master/src/main/java/com/rapidminer/operator/learner/tree/ParallelDecisionTreeLearner.java . Im a bit unsure where this comment pops up in studio.
~Martin
Dortmund, Germany
If you get the Weka extension (which is free and highly recommended, since it has over a hundred predictive modeling operators) then you will have access to several different flavors of decision tree operators, including the weka implementation of the C4.5 algorithm in the W-J48 operator.
Lindon Ventures
Data Science Consulting from Certified RapidMiner Experts
so I guess the C5.0 is not yet implemented in Rapidminer?
Hi
Where can i find C5 in Rapid Miner? It's not in the decision tree section?
You'll need to download the Weka extension to get it.
but I think C5.0 is too new and still under license to be implemented in rapidminer or weka yet, is that true?
its only C4.5 in Weka I think...
I am Thathar
shall I use C4.5 algorithm in Rapidminer?
hello @thatharpandi199 - I would use the normal Decision Tree operator in Studio Core. It is the best by far.
Scott