Ensemble Based Heart Disease Prediction Using Machine Learning

Authors

  • Minchala Siva Krishna  PG Scholar, Department of CSE, Vemu Institute of Technology, P. Kothakota, Chittoor, Andhra Pradesh, India
  • Mr. K. Naveen  Assistant Professor, Department of CSE, Vemu Institute of Technology, P. Kothakota, Chittoor, Andhra Pradesh, India

Keywords:

Machine learning, Classification Technique, Decision Tree, Random Forest Stacking Classifier, supervised machine learning.

Abstract

Clinical science has garnered significant attention from researchers due to their efforts in identifying early human mortality causes. The literature has confirmed that diseases can be caused by various factors, including heart-based disorders. To save human lives and assist healthcare professionals in recognizing, preventing, and managing heart disease, numerous researchers have proposed specific techniques.These techniques include the use of decision trees, random forests, XGBoost, and crossover models. The proposed approach dynamically analyzes the performance of each method, starting with the selection of the most appropriate strategy. The analysis involves implementing these approaches with different features to examine the statistics comprehensively. However, it is important to note that each successful plan has its own limitations. The goal is to build an intelligent and effective method through careful examination and refinement.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-08-30

Issue

Volume 9, Issue 4, July-August-2023

Section

Research Articles

License

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

How to Cite

[1]
Minchala Siva Krishna, Mr. K. Naveen, " Ensemble Based Heart Disease Prediction Using Machine Learning" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 4, pp.184-190, July-August-2023.