Heart Disease Risk Prediction Using Machine Learning Classifiers with Attribute Evaluators

Heart Disease Risk Prediction Using Machine Learning Classifiers with Attribute Evaluators

Cardiovascular diseases (CVDs) kill about 20.5 million people every year. Early prediction can help people to change their lifestyles and to ensure proper medical treatment if necessary. In this research, ten machine learning (ML) classifiers from different categories, such as Bayes, functions, lazy...

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Bibliographic Details
Main Authors: Karna Vishnu Vardhana Reddy, Irraivan Elamvazuthi, Azrina Abd Aziz, Sivajothi Paramasivam, Hui Na Chua, S. Pranavanand
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Applied Sciences
Subjects:
heart disease
data pre-processing
attribute evaluation
machine learning classifiers
hyperparameter tuning
Online Access:https://www.mdpi.com/2076-3417/11/18/8352

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https://www.mdpi.com/2076-3417/11/18/8352

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