An optimized Model for Heart Disease Prediction with Customized Ensemble Voting Classifier and Nature Inspired Optimization

Annwesha Banerjee Majumder; Somsubhra Gupta; Dharmpal Singh; Sourav Majumder

doi:10.17485/IJST/v16i34.1004

Article

An optimized Model for Heart Disease Prediction with Customized Ensemble Voting Classifier and Nature Inspired Optimization

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v16i34.1004

Year: 2023, Volume: 16, Issue: 34, Pages: 2719-2729

Original Article

An optimized Model for Heart Disease Prediction with Customized Ensemble Voting Classifier and Nature Inspired Optimization

Annwesha Banerjee Majumder^1*, Somsubhra Gupta², Dharmpal Singh³, Sourav Majumder⁴

¹Assistant Professor, Department of Information Technology, JIS College of Engineering, India
²Associate Professor, Department of Computer Science and Engineering, Swami Vivekananda University, India
³Associate Professor, Department of Computer Science and Engineering, JIS College of Engineering
⁴Manager, Capgemini, India

*Corresponding Author
Email: [email protected]

Received Date:10 May 2023, Accepted Date:03 August 2023, Published Date:14 September 2023

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Objective: To develop an optimized model for prediction of heart disease. Methods/findings: The model has been built applying Customized Ensemble Voting Classifier where the weights of each base classifier have been calculated considering accuracy, specificity and sensitivity. For feature selection Chi Square method has been applied. The performance of the model has been enhanced using Firefly algorithm. The proposed model has achieved 85.52% accuracy. Novelty: The novelty of our research paper on heart disease prediction lies in the integration of machine learning algorithms to develop an accurate predictive model. Multiple classifiers have grouped together through a customized ensemble voting classifier. For assigning the weight not only accuracy is considered but also specificity and sensitivity scores have also been considered and then performance has been optimized with Firefly algorithm which makes the method comprehensive and reliable for predicting heart disease risk and could ultimately lead to more effective prevention and treatment strategies.

Keywords: Chi Square; Ensemble Voting Classifier; Firefly Algorithm

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Copyright

© 2023 Majumder et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)