索引于
  • 学术期刊数据库
  • 打开 J 门
  • Genamics 期刊搜索
  • 期刊目录
  • 研究圣经
  • 乌尔里希的期刊目录
  • 电子期刊图书馆
  • 参考搜索
  • 哈姆达大学
  • 亚利桑那州EBSCO
  • OCLC-WorldCat
  • 学者指导
  • SWB 在线目录
  • 虚拟生物学图书馆 (vifabio)
  • 普布隆斯
  • 米亚尔
  • 日内瓦医学教育与研究基金会
  • 欧洲酒吧
  • 谷歌学术
分享此页面
期刊传单
Flyer image

抽象的

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.

免责声明: 此摘要通过人工智能工具翻译,尚未经过审核或验证