Optimizing Machine Learning Classifiers for Enhanced Cardiovascular Disease Prediction

Optimizing Machine Learning Classifiers for Enhanced Cardiovascular Disease Prediction

A key challenge in developing Machine Learning (ML) models for predicting or diagnosing Cardiovascular Disease (CVD), is selecting suitable algorithms and fine-tuning their parameters. In this study, we employed three ML techniques, namely Auto-WEKA, Decision Table/Naive Bayes (DTNB), and Multiobjec...

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Bibliographic Details
Main Authors: Sultan Munadi Alanazi, Gamal Saad Mohamed Khamis
Format: Article
Language:English
Published: D. G. Pylarinos 2024-02-01
Series:Engineering, Technology & Applied Science Research
Subjects:
Machine Learning (ML)
Auto-WEKA
Lazy IBK
DTNB
MOE fuzzy classifier
CVD
Online Access:https://etasr.com/index.php/ETASR/article/view/6684

Internet

https://etasr.com/index.php/ETASR/article/view/6684

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