The Altair Community is migrating to a new platform to provide a better experience for you. The RapidMiner Community will merge with the Altair Community at the same time. In preparation for the migration, both communities are on read-only mode from July 15th - July 24th, 2024. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here.
Options

Calculate Errors for leaf in a Decision Tree C4.5?

joandcruzjoandcruz Member Posts: 10 Contributor II
edited September 2019 in Help
Hi guys, I am trying to understand how Quinlan calculates the errors for leaf when pruning a decision tree. I have read his book on the subject and he says:

"For a confidence level CF, the upper limit on this probability can be found from the confidence limits for the binomial distribution. This upper limit here is written U_cf(E,N)"

where E is incorrectly classified events and N is total events in the leaf. He has a example with a confidence level of 25%, N=6 and E=0 and he calculates the error to U_25%(0,6) = 0.206. Could anyone explain how this is actually calculated? I have had no luck searching for it. Thank you for any help!

Answers

  • Options
    MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,525 RM Data Scientist
    Hi,

    could you give a bit more background? I am fully aware of the binomal distribution stuff, but i do not understand the example.


    Cheers,

    Martin
    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
Sign In or Register to comment.