alexa Dengue Fever Prediction: A Data Mining Problem
ISSN: 2153-0602

Journal of Data Mining in Genomics & Proteomics
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

Dengue Fever Prediction: A Data Mining Problem

Kamran Shaukat1*, Nayyer Masood2, Sundas Mehreen1 and Ulya Azmeen1

1IT Department, University of the Punjab, Jhelum Campus, Pakistan

2Mohammad Ali Jinnah University, Islamabad Campus. Pakistan

*Corresponding Author:
Kamran Shaukat
IT Department, University of the Punjab
Jhelum Campus, Pakistan
Tel: 0544-448770
E-mail: [email protected]

Received Date: June 04, 2015 Accepted Date: October 19, 2015 Published Date: October 25,2015

Citation: Shaukat K, Masood N, Mehreen S, Azmeen U (2015) Dengue Fever Prediction: A Data Mining Problem. J Data Mining Genomics Proteomics 6:181. doi: 10.4172/2153-0602.1000181

Copyright: © 2015 Shaukat K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Dengue is a threatening disease caused by female mosquitos. It is typically found in widespread hot regions. From long periods of time, Experts are trying to find out some of features on Dengue disease so that they can rightly categorize patients because different patients require different types of treatment. Pakistan has been target of Dengue disease from last few years. Dengue fever is used in classification techniques to evaluate and compare their performance. The dataset was collected from District Headquarter Hospital (DHQ) Jhelum. For properly categorizing our dataset, different classification techniques are used. These techniques are Naïve Bayesian, REP Tree, Random tree, J48 and SMO. WEKA was used as Data mining tool for classification of data. Firstly we will evaluate the performance of all the techniques separately with the help of tables and graphs depending upon dataset and secondly we will compare the performance of all the techniques.

Share This Page

Additional Info

Loading Please wait..
Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version