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Reduced conversion precision prevents model fitting
Describe the bug
The use of float32 precision in the X_to_numpy and y_to_numpy functions leads to numerical problems when fitting the elastic_net_cv forecaster. This reduced precision causes a ValueError in the sklearn api when computing the gram matrix
To Reproduce Tried unsuccessfully to reproduce it using random data.
**Desktop **
- OS: Windows 10
- Python: 3.10.0
- functime: 0.9.5
Additional context This issue seems related to the general precision problem discussed in scikit-learn#21997. A potential enhancement could be to allow configuration of precision level through an API option, improving the flexibility and applicability of the model in diverse scenarios.
