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May 25, 2024 22:10
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XGBoost Incremental Learning
Great example!
Few people know that xgboost is able to perform incremental learning by adding boosting rounds.
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Disregard, I figured it out. I was using handle_unknown='ignore' in OneHotEncoder, but one of the features has too few of a particular category, hence the mismatch.
Thank you for this gist. How can we implement this in a pipeline?
I am unable to test on the Boston dataset as it's been removed from sklearn, but on a different dataset I get a mismatch in number of columns. Even though I use the same pipeline the saved model seems to have one less feature than the new training data and I am unable to figure out why.