Indexé dans
  • Base de données des revues académiques
  • Ouvrir la porte J
  • Genamics JournalSeek
  • JournalTOCs
  • RechercheBible
  • Répertoire des périodiques d'Ulrich
  • Bibliothèque des revues électroniques
  • RechercheRef
  • Université Hamdard
  • EBSCO AZ
  • OCLC - WorldCat
  • érudit
  • Catalogue en ligne SWB
  • Bibliothèque virtuelle de biologie (vifabio)
  • Publions
  • MIAR
  • Fondation genevoise pour la formation et la recherche médicales
  • Pub européen
  • Google Scholar
Partager cette page
Dépliant de journal
Flyer image

Abstrait

Dengue Fever Prediction: A Data Mining Problem

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

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.

Avertissement: Ce résumé a été traduit à l'aide d'outils d'intelligence artificielle et n'a pas encore été examiné ni vérifié