Dublin Core
Title
A Comparison of Machine Learning Techniques in Predicting 10-year Risk of Coronary Heart Disease
Subject
Keywords: 10-year risk prediction, Heart study, Model building
Description
This study uses different supervised machine learning techniques to build models to predict the 10-year risk of Coronary heart disease using the Framingham heart study dataset. It compares, identifies, and selects the model with the highest prediction accuracy and the lowest test error rate.
Creator
Adeola M. Olaniyan
Contributor
No contributors
Format
PDF
Language
English
Type
Heart study: Model building, Risk prediction.
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