Predicting Early Hospital Readmission for Diabetic Patients.

[TheUsefulNerd]

Description

This PR introduces a complete Diabetes Readmission Prediction Model to the repository. The model is designed to predict the likelihood of diabetes patients being readmitted to the hospital based on various input features.

Issue Resolved

This PR resolves issue #17 , implementing a comprehensive solution for diabetes readmission prediction.

Checklist

• [x] My code follows the current project structure
• [x] I have thoroughly reviewed and updated the requirements.txt file to include any new packages
• [x] The predict.py file includes a properly implemented model_details() function, or the notebook contains this function to print a detailed model report. The model will not be accepted without this function, as it is essential for generating the necessary model details.
• [ ] I have added relevant tests (if necessary).
• [x] I have added comments in the code where needed.
• [x] This PR is submitted under Hacktoberfest.
• [x] This PR is submitted under GirlScript Summer of Code (GSSoC-Extd).

[TheUsefulNerd]

@yashasvini121, here it shows "this branch has conflicts that must be resolved." Is there something I can do?

[TheUsefulNerd]

The conflict was raised bcoz my code was extra in app.py. So, I just removed the markers so that my code add its urs. Is there anything else I can do?

[TheUsefulNerd]

@yashasvini121 can you review the PR today?

[TheUsefulNerd]

Give me 2 days of time. I am learning undersampling and oversampling. This time I will be focusing on getting a balanced recall. But, in the input there will be more that 25 to 30 features to be run by the model. It is because the category 2(minority class) has very less data compared to the majority class. But, I will try my best to enhance the performance.