A Critical Study of Selected Classification Algorithms for Dengue Fever and Dengue Hemorrhagic Fever
Frontiers of Information Technology (2013)
Islamabad, Pakistan Pakistan
Dec. 16, 2013 to Dec. 18, 2013
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FIT.2013.33
Dengue fever is viral infection caused by dengue virus which is transmitted in human body by bite of female Eddie mosquito. There are 50 million people suffer from it globally every year. Pakistan has been victim of this rapidly growing disease from last few years. The world health organization identified two main types of dengue fever. This paper appraises the selected classification algorithms for the classification of dengue fever (DF) and dengue haemraghic fever (DHF) datasets. Naïve Bayes classifier, Decision Tree, K-nearest neighbor algorithm, multilayered perception algorithm and Support vector machines are considered here for classification of dengue fever. These algorithms are measured based on five criteria: Accuracy, Precision, Sensitivity, Specificity and false negative rate.
Decision trees, Support vector machines, Accuracy, Classification algorithms, Sensitivity, Pain, Hospitals,dengue fever, Dataminingmining, supervised machine learning
Wajeeha Farooqi, Sadaf Ali, "A Critical Study of Selected Classification Algorithms for Dengue Fever and Dengue Hemorrhagic Fever", Frontiers of Information Technology, vol. 00, no. , pp. 140-145, 2013, doi:10.1109/FIT.2013.33