This project aims to build a classification model that will predict whether Diabetic patients will be readmitted within 30 days. The Hospital Readmission Program (HRRP) reduces hospital fundings if diabetic patients readmission in less than 30 days rate above average. The ability to intervene early when a patient is at risk of readmission is crucial for hospital management. We can use machine learning models to predict and prioritize these patients. We will develop and evaluate four models in this paper: Naïve Bayes, Logistic Regression, Knn, and SVM. Results will then be compared and analyzed. Finally, the best-performing model will be selected.
In ths repositorie you will find:
The dataset Data Engineering and analysis (preprocessing and exploratory analysis) Model Training Selection process. Final Paper with analysis and conclusions