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Poster
in
Affinity Workshop: Black in AI

Comparison of Classification Algorithms for Predicting Completeness of Measles Vaccination

Peter Oseghale Ohue · Oluyemi Adewole Okunlola

Keywords: [ Applications of AI to Health ] [ machine learning ]


Abstract:

Supervised machine learning (ML) algorithms are efficient at predicting the occurrence of diseases and they have become more popular as a result of the recent pandemic. A global re-emergence of measles has been reported and with the help of complete vaccination measles can be prevented. An average accuracy score of 0.90 confirms the predictive capacity of ML models. In terms of performance RFC, LDA and LR performed better than CART and KNN.

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