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首页> 外文期刊>International journal of computer science and network security >Feature Selection for Prediction of HIV/AIDS using Data Mining Technique by Applying the Concept of Theory of Evidence
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Feature Selection for Prediction of HIV/AIDS using Data Mining Technique by Applying the Concept of Theory of Evidence

机译:运用证据理论概念通过数据挖掘技术预测艾滋病毒/艾滋病的特征选择

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摘要

The devastating disease HIV is well known as being the cause for development of Acquired Immunodeficiency Syndrome (AIDS). In the last 2 decades, over 60 million people have been infected with HIV, most of the people are identified and infected by HIV in the developing countries. In this paper Dempster Shafer (DS) theory is focused to identify the hidden information from the data set using the concept theory of evidence. The dataset are collected from the different Non-Government Organizations (NGO) and Government organizations of India. To analyze the dataset in particularly nearby areas of Vellore District of Tamil Nadu , India, the DS theory is used and to select the important attributes available in the dataset in order minimize the size of the data set.
机译:众所周知,破坏性疾病HIV是导致后天免疫机能丧失综合症(AIDS)的原因。在过去的20年中,已经有超过6000万人感染了艾滋病毒,在发展中国家,大多数人被识别并感染了艾滋病毒。在本文中,Dempster Shafer(DS)理论致力于使用证据的概念理论从数据集中识别隐藏信息。该数据集来自印度不同的非政府组织(NGO)和政府组织。为了分析印度泰米尔纳德邦韦洛尔区特别是附近地区的数据集,使用了DS理论并选择了数据集中可用的重要属性,以最小化数据集的大小。

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