TheAlgorithms
Create error handling function in linear regression algorithm of ML
What would you like to share?
We can add error handling function to the linear regressio algorithm in the ML folder; so that it can handle errors and still run the linear regression algorithm
Additional information
No response
The linear regression algorithm in this repo should be reimplemented anyway (see #8847). As such, this additional handling should be either incorporated into the reimplementation PR or saved for a later PR.
In any case, what sort of error handling are you suggesting? Input validation, floating-point errors, etc?
Hi! I would love to work on this issue and improve the robustness of the linear_regression.py script by adding appropriate error handling (e.g., input validation, type checking, missing data, etc.).
Please let me know if this is still open for contribution or if the file will be replaced soon so I can plan accordingly. Either way, I’d be happy to help!
