🎉Community Raffle - Win $25

An exclusive raffle opportunity for active members like you! Complete your profile, answer questions and get your first accepted badge to enter the raffle.
Join and Win

"Decision Tree Optimization and Accuracy"

User: "lex_"
New Altair Community Member
Updated by Jocelyn

Hi,

 

I'm trying to use a decision tree which is nested inside the Optimize Parameters (Grid), focusing on Max. Depth and Min. Gain.

 

 

Reconstructing the decision tree using the results obtained above, but without the Optimize Parameters (Grid), the accuracy is lower now.

 

Why is that so?

Find more posts tagged with

Sort by:
1 - 3 of 31

    Hi,

     

    what performances are you comparing? The X-Val performances from within the optimization with an X-Val result from without?


    Are the performances comparable w.r.t their std_devs?


    ~Martin

    User: "Telcontar120"
    New Altair Community Member
    Accepted Answer

    If you are using cross-validation without a local random seed set then every time you close and re-open that process in RapidMiner you can get a different result even if you don't make any other changes.  So I suspect that could be the issue.  

     

     

    User: "lex_"
    New Altair Community Member
    OP

    Thanks for pointing me to the right direction.

     

    The random seed was the issue, resulting in the data sets being different after the split operator.