Model Outputs Consistency

kautuk
kautuk Partner, Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 5 Partner

Hi,

I am trying to build a model on Dataiku platform using AutoML inside Lab. If I give same parameters settings to the model multiple times, I am getting a slightly different output each time. I wanted to know if there is a way to get the consistent outputs from the model in each run (similar to set.seed in python).

Thanks,

Kautuk


Operating system used: Chrome

Answers

  • Alexandru
    Alexandru Dataiker, Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 1,226 Dataiker

    Hi @kautuk
    ,

    When splitting the Train/Test set a random fixed seed is already defined:

    Screenshot 2022-09-17 at 13.58.04.png

    Can you confirm what settings you are using train/test split?

    Are you seeing the same result with an explicit extract from 2 datasets?

  • kautuk
    kautuk Partner, Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 5 Partner

    Hi @AlexT
    ,

    Thanks for the response. I am using ' Explicit extracts from two datasets' Policy and not using train-test split from the same dataset. And, yes, the results are different each time,

  • Alexandru
    Alexandru Dataiker, Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 1,226 Dataiker

    Depending on the algorithm type, some variance can happen.

    I think it's best to continue looking into this if you via a support ticket.

    Please share the model type and screenshots and any sample of data you can share in the support to ilustrate this variance when scored.

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