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 |