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Each year Dengue infection causes havoc almost across the entire globe raising the death toll and thus becoming a global burden. With the absence of Global approved vaccine and its scope not limiting itself to tropical regions anymore, it has become a rapidly growing epidemic. Researchers have comprehensively explored mechanisms to predict and diagnose infectious diseases and machine learning has revolutionized the medical field by reducing the computing time in analyzing complex data and finding hidden patterns for accurate predictions. In this study, a comparative machine learning-based analysis is achieved using python based classification to predict dengue fever infection in a person. This paper helps interested researchers choose the most efficient classification technique among the selected machine learning classifiers by not only focusing on accuracy achieved but on overall classification metrics analysis to develop a better Dengue predictive model.
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