Support for LGBM Booster models #403
Labels
Enhancement
Type: enhancement (new feature or request)
Needs decision
The MAPIE team is deciding what to do next.
Other or internal
If no other grey tag is relevant or if issue from the MAPIE team
Source: contributors
Proposed by contributors.
Conformal prediction in MAPIE using existing models (e.g. https://mapie.readthedocs.io/en/latest/examples_regression/1-quickstart/plot_prefit.html#sphx-glr-examples-regression-1-quickstart-plot-prefit-py) supports models which have fit and predict attributes only. However, LGBM Regression models saved to disk, either using Booster method or pickle, don't have a "fit" attribute but a "refit" attribute (https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.Booster.html#lightgbm.Booster.refit). Unfortunately, MAPIE seems unable to use the refit method. Therefore, at this point, an LGBM Booster instance seems to be incompatible with MAPIE.
Enabling compatibility between LGBM Booster and MAPIE could be very useful for instances where a model is reused multiple times for prediction in the future and fitting a model from scratch is not possible.
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