Model Outputs Consistency
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
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Alexandru Dataiker, Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 1,353 DataikerHi @kautuk
,When splitting the Train/Test set a random fixed seed is already defined:
Can you confirm what settings you are using train/test split?
Are you seeing the same result with an explicit extract from 2 datasets?
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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,
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Alexandru Dataiker, Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 1,353 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.