I’m trying to make sure my xgboost python models are the same when generated using the same [random_state, seed, input features, model params]. However, although the decision-trees are exactly the same (assessed visually using plot_tree), the binary files that are stored on two different Windows machines are different.
I compare models using the “diff” command.
The models are the same as long as they’re run on the same machine, but they’re different when I switch machines.
So far I’ve tried:
- Using pickle instead of sklearn.externals.joblib to dump the models.
- creating the exact same conda environment for the two machines.
Any idea what might be causing this?