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[jvm-packages] the classification model trained by xgboost4j-spark is xgboost in-compatible #7895

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Tracked by #7802
wbo4958 opened this issue May 13, 2022 · 0 comments · Fixed by #7896
Closed
Tracked by #7802

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@wbo4958
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wbo4958 commented May 13, 2022

When saving XGBoostClassificationModel, XGBoostClassificationModel will add the num class into the beginning of the xgboost native model resulting in the model being xgboost in-compatible, which means xgboost native/xgboost python can't load the model trained from XGBoost4j directly.

Although XGBoostClassificationModel provides a way to produce the XGBoost native model by

model.nativeBooster.saveModel(model_path)

But it's really un-convenient to add extra step to get the model.

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