Comments (3)
izeigerman
commented on May 12, 2024
Hi @gnodabb ! Thanks for reporting this issue. This is expected behavior, since m2cgen expects the sklearn wrapper to be passed instead of a booster object. The corresponding wrappers are: lightgbm.LGBMRegressor and lightgbm.LGBMClassifier for regression and classification accordingly. Can you try passing either of these into m2c.export_to_c instead?
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gnodabb
commented on May 12, 2024
Gotcha! Thank you! Sorry for the inconvenience. Awesome tool!
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izeigerman
commented on May 12, 2024
@gnodabb no problem at all, I'm glad my suggestion helped. Happy to hear that you enjoy using m2cgen! Closing the issue now.
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Related Issues (20)
- Support export to new languages
- Support export of new ML models
- I am getting an error NotImplementedError: Model 'lightgbm_Booster' is not supported while loading a lightgbm model file. HOT 1
- Support for SAS - happy to open PR with some guidance HOT 4
- Accuracies totally different HOT 3
- The converted C model compiles very slow,how can i fix it?
- Unable to export LGBM model that uses `categorical_feature` HOT 2
- Convert ML model to c# HOT 2
- Issue with xgboost export in python: not same values splits HOT 1
- Getting predict_prob when convert m2cgen to different languages
- Feature Request: support for multioutput regression HOT 1
- Process ended with exit code -1073741571 (0xC00000FD) HOT 1
- Results dont match
- Add Fortran
- LightGBM models
- Unable to export code from XGBoost 1.7.5 models HOT 6
- How to use model for jpg photo?
- Issue while Exporting a LightGBM Model to C#
- XGBoost exported to C generates wrong indices for input array
- Logitraw objective function ignored for xgb.Booster
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