Comments (4)
yungcero
commented on June 20, 2024
Found some bugs when walking through the source code in regards to how spark handles the model conversion - will work a fix and push up a MR for review
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yungcero
commented on June 20, 2024
Going to clean up the spark code on our forked repo then will open a pull request to merge back into the main onnxtools
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xadupre
commented on June 20, 2024
I'll close this since the PR fixing it was merged.
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yungcero
commented on June 20, 2024
Awesome. Thank you and sounds good! @xadupre
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Related Issues (20)
- errror:'Booster' object has no attribute 'attr' HOT 5
- Convert_xgboost for XGBRegressor with objective="reg:logistic" gives wrong results
- Inference performance issues with Lightgbm when using categoricals HOT 1
- Trying to export MultiOutputRegressor(LGBMRegressor()) to onnx
- XGBoost 2.0.0 breaking changes HOT 3
- cannot import name 'FEATURE_IMPORTANCE_TYPE_MAPPER' from 'lightgbm.basic' HOT 5
- XGBRegressor with objective='count:poisson' causes serialization to fail with no error message HOT 1
- Please help validate release candidate for ONNX 1.15.0rc1 HOT 1
- What version of TensorFlow is supported by onnxmltools？ HOT 1
- `XGBRFClassifier` & `XGBRFRegressor` are not supported HOT 22
- `TreeEnsembleRegressor` introduces an additional batch dimension HOT 2
- Mismatch between XGBoost and converted onnx, with respect to "colsample_bytree"
- XGBoost best_ntree_limit is removed in 2.0 and trying to access this value HOT 1
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- onnx converted : xgboostRegressor multioutput model predicts 1 dimension instead of original 210 dimensions. HOT 3
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