Problem Statement: Predict whether a patient has heart disease based on given medical factors using machine learning classification techniques. Evaluate the model using accuracy, precision, recall, and confusion matrix heatmaps.
Heart disease is a leading cause of mortality worldwide. Early prediction using machine learning models can help in timely diagnosis and treatment. This project aims to classify patients into two categories — with and without heart disease — based on several medical input features.
We'll use a dataset that includes features like age, cholesterol level, resting blood pressure, chest pain type, and more to train and evaluate classification models.