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Prediction of Dengue Fever Outbreaks using Machine Learning Methods
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 46 |
| Year of Publication: 2022 |
| Authors: Ponnada Akhil, A. Ajaya Kumar |
10.5120/ijca2022921867
|
Ponnada Akhil, A. Ajaya Kumar . Prediction of Dengue Fever Outbreaks using Machine Learning Methods. International Journal of Computer Applications. 183, 46 ( Jan 2022), 52-56. DOI=10.5120/ijca2022921867
Abstract
Mosquitoes are the major source of the spread of dengue. The blood sample of a person is mostly used for detection of dengue. But there are various other factors which are responsible for dengue prevalence.In this project,weather conditions such as dew point, humidity, minimum and maximum temperatures along with precipitation of places present in India are considered to predict whether dengue exists or not. The four supervised algorithms- k-nearest neighbors, random forest, decision tree and support vector machines are compared to predictions. The results of these algorithms are compared based on accuracy, precision, and recall.
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