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A Comparative Study on Prediction of Dengue Fever Using Machine Learning Algorithm

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dc.contributor.author Dourjoy, Saif Mahmud Khan
dc.contributor.author Rafi, Abu Mohammed Golam Rabbani
dc.date.accessioned 2020-11-16T10:08:30Z
dc.date.available 2020-11-16T10:08:30Z
dc.date.issued 2019-12-07
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/5089
dc.description.abstract Dengue is one of the most common viral fever to the people. This is also known as life threatening disease. Dengue has become more and more evident this year in Bangladesh. It has taken the lives of many in our country. And the number of dengue fever patients is increasing day by day. There are many people is at risk from dengue. Early forecast of dengue can spare individual's life by cautioning them to take legitimate conclusion and care. But it is difficult to say in advance whether this will happen or not. The aim of this piece of research work is to analysis the symptoms of dengue fever and early prediction of the symptoms that can be seen in years ahead. For predicting the symptoms two different machine learning algorithms have been used. Support vector machine (SVM) and random forest classifier algorithm have been used. Finally the accuracy of these two has been evaluated and the confusion matrix has been shown. And then we have talked about the algorithm which is better for our dataset. en_US
dc.language.iso en en_US
dc.publisher Daffodil International University en_US
dc.subject Machine Learning en_US
dc.subject Dengue Fever en_US
dc.title A Comparative Study on Prediction of Dengue Fever Using Machine Learning Algorithm en_US
dc.type Other en_US

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