💡[Feature]: Diabetes Prediction with Neural Network #1477
Description
Is there an existing issue for this?
- I have searched the existing issues
Feature Description
I would like to propose adding a new feature to enhance the Diabetes Prediction with Neural Network project by expanding its capabilities. The project currently uses an MLPClassifier to predict whether a patient has diabetes based on diagnostic data.
The feature enhancement would include:
- Hyperparameter
- Cross-validation
- Model Evaluation Metrics
Additionally, I will include the necessary .csv file, requirements.txt, and README.md files to ensure the project is fully documented and easy to set up. This will make the project more accessible and easier to reproduce for new users.
Use Case
This feature would enhance the project by allowing for a more robust and optimized model. The ability to tune hyperparameters and evaluate the model with more metrics would benefit users looking to improve prediction accuracy for diabetes and gain deeper insights into model performance.
In a real-world scenario, where medical decisions are critical, this feature would allow practitioners or data scientists to optimize the model further for better predictive outcomes, potentially improving patient diagnosis and care.
Assign this issue to @ananas304 with appropriate tags.
Thankyou for your time :)
Benefits
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Add ScreenShots
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Priority
Medium
Record
- I have read the Contributing Guidelines
- I'm a GSSOC'24 contributor
- I want to work on this issue