Performance Evaluation of Machine Learning Algorithms for Dengue Disease Prediction

Abstract

Dengue is a dangerous disease caused by female mosquitoes. Dengue fever (also called as breakbone fever) is a infection that can cause to a severe illness which is happened by four different viruses and spread by Aedes mosquitoes. It is the necessary to devise effective methodology for dengue disease prognosis. Machine learning is a sub-filed of artificial intelligence (AI) which offers systems the ability to learn and improve from experience without human intervention and being explicitly programmed. In this research work, the performance analysis of various prediction models is done for dengue disease prediction. It is observed that C4.5 algorithm outperforms well in terms of performance measures such as accuracy (89.33%), prediction (88.9%), recall (89.77%) and other measures.