Chronic Kidney Disease Prediction

Comparative ML analysis: Naive Bayes, SVM, and Random Forest for early CKD detection.

Dataset

UCI Machine Learning Repository — 400 patients, 25 features, binary classification (CKD / Not CKD)

Models & Results

Model	Accuracy
Random Forest	Best performer
Naive Bayes	Lightweight alternative
Optimized SVM	Robust for complex patterns

Tech Stack

Python, scikit-learn, Pandas, Matplotlib, Seaborn

How to Run

pip install -r requirements.txt jupyter notebook notebooks/ckd_analysis.ipynb