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MapieQuantileRegressor with prefit model from Keras/Tensorflow #448

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dani-vu opened this issue May 24, 2024 · 1 comment
Open

MapieQuantileRegressor with prefit model from Keras/Tensorflow #448

dani-vu opened this issue May 24, 2024 · 1 comment
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Enhancement Type: enhancement (new feature or request) Source: contributors Proposed by contributors.

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@dani-vu
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dani-vu commented May 24, 2024

I want to apply CQR with a customized LSTM model created with Tensorflow. However, it does not support Tensorflow models. Is there a workaround or am I missing something?

Thanks!

@dani-vu dani-vu added the Enhancement Type: enhancement (new feature or request) label May 24, 2024
@LacombeLouis
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Hey @dani-vu,
Thank you for the issue. I believe that if you use the cv="prefit" you should be able to use MapieQuantileRegressor by simply packaging your models as in the issue #340. Note that you need to fit all three models and provide them as follows:

    estimators_: List[RegressorMixin]
        - [0]: Estimator with quantile value of alpha/2
        - [1]: Estimator with quantile value of 1 - alpha/2
        - [2]: Estimator with quantile value of 0.5

Don't hesitate if you have any other question!

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Labels
Enhancement Type: enhancement (new feature or request) Source: contributors Proposed by contributors.
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