Increasing the reliability of Heart Disease classification models using Class Balancing techniques with Feature Engineering
Neeraj Sharma,
Praveen Lalwani
Abstract:In this article, we explore the natural problem of class imbalance in the heart disease datasets. Aiming for a comprehensive examination of the class balancing techniques we train and test our models on three different datasets all suffering from different degree of class imbalance. The Healthcare dataset (mid size) and the BRFSS-2015 dataset (large dataset) having huge class imbalance, and the Iraq hospital dataset with mild class imbalance. Feature selection is done using backward elimination and Logistic Re… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.