Comments (2)
miceno
commented on May 18, 2024
Hi,
We also noted this tolerance. Is there any way to improve it?
Thank you!!!
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cpfarrell
commented on May 18, 2024
I would recommend to always be using features as floats. XGBoost is explicit that it treats things as 32 bit due to performance optimizations (one example dmlc/xgboost#1410). If a model has been trained using xgboost its split values will be stored as floats and so giving it doubles may cause inaccurate predictions if hit just the right values.
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