"multiple learners in AdaBoost"

Elisa0815Elisa0815 MemberPosts:10Contributor I
edited June 2019 inHelp
I have a question about the AdaBoost operator.

As I understood AdaBoost in several literature, AdaBoost uses, for every iteration, another simple base classifier for classification. But in RapidMiner Studio, only one learner can be chosen for AdaBoost.

Did I may understand AdaBoost wrong? Why can only one learner be chosen? That doesn't fit to my understanding of AdaBoost and confuses me. ???

Would be great, if anyone could may help.

Greets
Elisa
Tagged:

Answers

  • MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts:3,381RM Data Scientist
    Well, it is another instance of the same base learner.

    So you always train e.g. a Decision tree but on differently weighted data. So the result are different decision trees.

    ~Martin
    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany
Sign InorRegisterto comment.