The Altair Community is migrating to a new platform to provide a better experience for you. In preparation for the migration, the Altair Community is on read-only mode from October 28 - November 6, 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
Calculate Errors for leaf in a Decision Tree C4.5?
Contributor I
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!
"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!
Tagged:
0
Answers
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
Dortmund, Germany