Vaccination is a proactive medical immunization procedure where an inactivated
form of a disease-causing agent (such as a virus) is administered to boost the body's defense
systems. Efficient management of vaccination status is crucial in healthcare management, disease
eradication, community immunity ("herd immunity"), disease prevention, and global health
security. Ensuring precise monitoring and validation of an individual's vaccination status is
indispensable, especially in the context of emerging diseases and epidemics. This study
evaluates the likelihood of individuals obtaining vaccination for the H1N1 virus and the
seasonal flu vaccine. Ensemble methods combine the predictions of multiple base classifiers to
enhance overall performance. One such method, the hard voting classifier, aggregates the votes
from each base classifier and selects the class with the majority vote as the final prediction.
This approach leverages the strengths of different classifiers, reducing the risk of individual
model biases and improving generalization using metrics such as precision, recall, accuracy, and
F1-score are employed to assess the system's effectiveness. The results demonstrate how
data-driven methods can address population wellness and improve vaccination rates using an
ensemble method. The proposed ensemble hard voting classifier achieved accuracies of 0.905 and
0.907 on the H1N1 and seasonal vaccine datasets, respectively. Using an ensemble approach like
the hard voting classifier enhances prediction accuracy and robustness, ultimately leading to
better decision making in public health initiatives.
Keywords
Classification, Voting Classifier, Preprocessing, Model Selection, Public Health,
Performance Analysis, Vaccination Status, Accuracy, Linear Regression, Structured Data.
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Acknowledgements
Author(s) thanks to Dr.Agusthiyar R for this research completion and support.
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The authors would like to thank to the reviewers for nice comments on the
manuscript.
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Corresponding author
Agusthiyar R
Agusthiyar R
Department of Computer Science and Application, SRM Institute of Science and
Technology, Ramapuram, Chennai, India.
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Cite this article
Saranya S and Agusthiyar R, “Classification of an Individuals Vaccination Status
Using Ensemble Hard Voting Classifier”,
Journal of Machine and Computing, pp. 980-991, October 2024. doi:10.53759/7669/jmc202404091.
