[BUG] GridSearchCV Warning: Non-Finite Test Scores for SVR Model

[shristirwt]

Has this bug been raised before?

• I have checked "open" AND "closed" issues and this is not a duplicate

Description

I am encountering a warning during the hyperparameter tuning of a Support Vector Regression (SVR) model using GridSearchCV in scikit-learn. The warning states: "One or more of the test scores are non-finite: [nan nan nan nan nan nan]."
Another warning occured when attempting to define a Keras Sequential model. The warning indicates that the model is improperly configured by passing the input_shape directly to the Dense layers rather than using an Input layer at the beginning of the model.

Steps to Reproduce

Include any relevant details like:

• What page you were on... stock_market(complete).ipynb
• What you were trying to do... I was executing the code when I encountered the warning
• What went wrong... It displayed the above mentioned warnings

Screenshots

No response

Do you want to work on this issue?

Yes

If "yes" to the above, please explain how you would technically implement this.

I will switch the scoring metric to a regression-appropriate metric and for the second warning I will use Input layer

[github-actions]

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[Mayureshd-18]

@shristirwt Assigned!

[github-actions]

✅ This issue has been successfully closed. Thank you for your contribution and helping us improve the project! If you have any more ideas or run into other issues, feel free to open a new one. Happy coding! 🚀