Constructing Eigenvalue/Coefficient Feature Vectors for Heart Attack Classification

Abstract

We describe a method of constructing feature vectors from EKG data for use in classical machine learning algorithms. This method uses eigenvalues from transforming the data set into a system of linear differential equations. We find that this method is efficient, easy to implement, and results in accuracy over 90%.