Dengue Fever Prediction: A Data Mining Problem

K. Shaukat, N. Masood, S. Mehreen, Ulya Azmeen
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引用次数: 53

Abstract

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 Naive 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.
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登革热预测:一个数据挖掘问题
登革热是一种由雌蚊引起的威胁性疾病。它通常在广泛的炎热地区发现。长期以来,专家们正试图找出登革热的一些特征,以便正确地对患者进行分类,因为不同的患者需要不同的治疗方法。过去几年来,巴基斯坦一直是登革热的目标。登革热被用于分类技术,以评估和比较它们的性能。数据集收集自Jhelum区总部医院(DHQ)。为了正确地对数据集进行分类,使用了不同的分类技术。这些技术是朴素贝叶斯,REP树,随机树,J48和SMO。使用WEKA作为数据挖掘工具对数据进行分类。首先,我们将根据数据集分别使用表格和图形来评估所有技术的性能,其次,我们将比较所有技术的性能。
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