Introduction
This project proposes a comparative analysis of several popular classification methods using a unique dataset compiled from five distinct heart disease datasets: Cleveland, Hungarian, Switzerland, Long Beach VA, and Statlog (Heart) Data Set. (Dataset link https://www.kaggle.com/datasets/mexwell/heart-disease-dataset)

Objectives
The primary objective of this project is to evaluate and compare the effectiveness of various classification techniques in predicting heart disease. The methods to be evaluated include:
1. Logistic Regression (potentially using Bayesian Lasso)
2. Random Forest
3. Decision Tree
4. K-Nearest Neighbors (KNN)
5. maybe more