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combination of decision trees?
SabaMomeniKho
Learner III
in Help
Hello to all. Is there any way in rapidminer that we could combine multiple decision trees together in order to reach a more comprehensive tree (I guess) ?! I've heard that this cand be done for big data and I was wondering if it is possible to be done in rapidminer.
thank you
thank you
2
Best Answers
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varunm1
Unicorn
Hello @SabaMomeniKho
Does "group models" operator suffice your needs?
https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/group_models.html
If you are looking for bagging and boosting there are "bagging" & "Adaboost" operators as well.
If you are looking for something more specific, please provide relevant details.Regards,
Varun
https://www.varunmandalapu.com/Be Safe. Follow precautions and Maintain Social Distancing
6 -
rfuentealba
Unicorn
Hello, @SabaMomeniKhoAnother operator I normally use is "Vote" to mix a few decision trees and choose which one to use, besides AdaBoost, bagging and group models as my good friend @varunm1 already suggested.It depends on what kind of interaction do you need on the models.All the best,Rod.7
Answers
https://academy.rapidminer.com/learn/article/ensemble-models-diversity-works-like-magic
you can watch this video too
Regards,
mbs
also you have this one
https://community.rapidminer.com/discussion/56823/adaboost-bagging-bayesian-boosting-classification-by-regression#latest
Good luck
be careful with Group Models. It's not applicable in this situation.
The help text says:
Group Models is helpful for chaining preprocessing models (Normalize, PCA, Nominal to Numerical etc.) and then adding *one* predictive model. The result will be a combined model that does the preprocessing in the way it was set up, but can be handled (stored/retrieved/applied) as one model.
Regards,
Balázs
Varun
https://www.varunmandalapu.com/
Be Safe. Follow precautions and Maintain Social Distancing
If you need more information about this operators please let me know I will help you
Regards
mbs