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Decision Tree Operator - C5 or C4.5 algorithm?

cwerningcwerning Member Posts: 10 Contributor II
edited November 2018 in Help

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

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Best Answer

  • MartinLiebigMartinLiebig Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,533 RM Data Scientist
    Solution Accepted

    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, Germany

Answers

  • cwerningcwerning Member Posts: 10 Contributor II

    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

  • MartinLiebigMartinLiebig Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,533 RM Data Scientist

    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

    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
  • Telcontar120Telcontar120 RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,635 Unicorn

    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.

    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
  • Fred12Fred12 Member Posts: 344 Unicorn

    so I guess the C5.0 is not yet implemented in Rapidminer?

  • accounting1100accounting1100 Member Posts: 1 Learner III

    Hi

     

    Where can i find C5 in Rapid Miner? It's not in the decision tree section?

  • Thomas_OttThomas_Ott RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,761 Unicorn

    You'll need to download the Weka extension to get it. 

  • Fred12Fred12 Member Posts: 344 Unicorn

    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...

  • thatharpandi199thatharpandi199 Member Posts: 1 Learner II

    I am Thathar

    shall I use C4.5 algorithm in Rapidminer?

  • sgenzersgenzer Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 Community Manager

    hello @thatharpandi199 - I would use the normal Decision Tree operator in Studio Core. It is the best by far. :)


    Scott

     

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