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.
Describe the bug The use of
float32precision in theX_to_numpyandy_to_numpyfunctions 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 matrixTo Reproduce Tried unsuccessfully to reproduce it using random data.
Desktop
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.