XGBoost Tree Learner: Random Seed Issue

Hi all,

I used Knime to make a predictive classification model using different tree-based models like RF, XGBoost and … With RF, every time that I run the model, I get different results which makes sense as I didn’t used a static random seed. However, with XGBoost (Tree Ensemble Learner node), every time I run the model, I still get same output with exactly same probabilities. I’m not sure what could be the issue as everything looks fine with RF but not with XGBoost. Has anybody experienced a same issue with XGBoost nodes/workflows?
I should also mention that I need to run the model several times to get the probability for each prediction to calculate uncertainty.

Thanks!

Have you checked the node settings to ensure random seed is not set by default?
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