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"multiple learners in AdaBoost"

Elisa0815Elisa0815 Member Posts: 10 Contributor II
edited June 2019 in Help
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
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Answers

  • MartinLiebigMartinLiebig Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,533 RM 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
    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
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