"Boosted Decision Tree"

TimboTimbo Member Posts: 14 Contributor II
edited May 2019 in Help

I am trying to put together a Boosted Decision Tree of the following form:

--> Boosting Algorithm(Ada or Bayesian Boosting... well probably Ada)
-----> Some kind of Decsion Tree (as inner operator)

Now here's the problem with that:

When I use a simple Decision Tree I get the following message: "Input example set has example weights, but the learner will ignore them."
When I use a weight based DT it requires an inner operator, so this seems to be no good choice either?

Does anyone know a way out of this?


  • landland RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,531 Unicorn
    the solution is simple: Ignore the warning. The tree can handle this although notifying this. Will be corrected with the next version.

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