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"Boosted Decision Tree"
Contributor II
Hi,
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?
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?
Tagged:
0
Answers
the solution is simple: Ignore the warning. The tree can handle this although notifying this. Will be corrected with the next version.
Greetings,
Sebastian