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Using optimize parameters(Grid) on decision tree

Ben_SuenBen_Suen Member Posts: 3 Learner I
edited June 2019 in Help
Hi,

I used optimize parameters(Grid) to determine the optimal parameters used in decision tree. The result give me something like maximal_depth=14, minimal leaf size=92. But when i look in the model, i found that there are some leafs containing only 1 sample. Do anyone know if i did something wrong? 

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    Telcontar120Telcontar120 Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,635 Unicorn
    Also did you actually optimize minimal leaf size parameter or minimal size for split?  They work a bit differently.
    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
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    Ben_SuenBen_Suen Member Posts: 3 Learner I
    Hi @Telcontar120
    I optimized minimal leaf size parameter. i think there should be at least 92 sample in each leaf after the optimize parameter operator give me these parameter. Do i misunderstand something here? 
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    Telcontar120Telcontar120 Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,635 Unicorn
    @Ben_Suen can you post your process xml for us to review? I think @mschmitz whether or not the model is overtuned (although I agree with you) is a somewhat separate issue.  If the tree is resulting in notes that are smaller than the minimal leaf size parameters it sounds like it could be a bug.
    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
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