Using optimize parameters(Grid) on decision tree

Ben_Suen
Ben_Suen New Altair Community Member
edited November 2024 in Community Q&A
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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Best Answer

  • MartinLiebig
    MartinLiebig
    Altair Employee
    Answer ✓
    did you use a validation scheme like cross-validation? This sounds a bit over-trained.

    Best,
    Martin

Answers

  • MartinLiebig
    MartinLiebig
    Altair Employee
    Answer ✓
    did you use a validation scheme like cross-validation? This sounds a bit over-trained.

    Best,
    Martin
  • Telcontar120
    Telcontar120 New Altair Community Member
    Also did you actually optimize minimal leaf size parameter or minimal size for split?  They work a bit differently.
  • Ben_Suen
    Ben_Suen New Altair Community Member
    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? 
  • Telcontar120
    Telcontar120 New Altair Community Member
    @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.

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