Heart-Disease-Prediction

The project involved analysis of the heart disease patient dataset with proper data processing. Then, different models are trained and predictions are made with different algorithms. They are:

1. K-Nearest Neighbor (KNN)
2. Decision Tree Classifier
3. Random Forest Classifier
4. Support Vector Machine (Linear)
5. LightGBM Classifier

I've used a variety of Machine Learning algorithms, implemented in Python, to predict the presence of heart disease in a patient. This is a classification problem, with input features as a variety of parameters, and the target variable as a binary variable, predicting whether heart disease is present or not.

Dataset Used: https://www.kaggle.com/ronitf/heart-disease-uci