Data Analysis Methods Final Project

Project Introduction

For this project, our goal is to classify the possible complications of a myocardial infarction (MI), or heart attack based on various patient attributes. The dataset we will be using is from the UCI Machine Learning Repository, and it contains data from 1992-1995 for 1700 patients in Krasnoyarsk, Russia. There are 111 patient attributes and 12 possible complications of MI included in the dataset. The techniques that will be used for our classification models are Random Forest and kNN. After creating two different classication models, we will compare and analyze them.
Dataset: UCI Myocardial Infarction Complications