文章基本信息

标题：Heart Disease Prediction Using Frequent Item Set Mining and Classification Technique
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作者：Sinkon Nayak ; Mahendra Kumar Gourisaria ; Manjusha Pandey 等
期刊名称：International Journal of Information Engineering and Electronic Business
印刷版ISSN：2074-9023
电子版ISSN：2074-9031
出版年度：2019
卷号：11
期号：6
页码：9-15
DOI：10.5815/ijieeb.2019.06.02
出版社：MECS Publisher
摘要：The heart is the most important part of the human body. Any abnormality in heart results heart related illness in which it obstructs blood vessels which causes heart attack, chest pain or stroke. Care and improvement of the health by the help of identification, prevention, and care of any kind of diseases is the main goal. So for this various prediction analysis methods are used which job is to identify the illness at prelim phase so that prevention and care of heart disease is done. This paper emphasizes on the care of heart diseases at a primitive phase so that it will lead to a successful cure. In this paper, diverse data mining classification method like Decision tree classification, Naive Bayes classification, Support Vector Machine classification, and k-NN classification are used for determination and safeguard of the diseases.
关键词：Heart Disease;Frequent Itemset;Classification;Performance Measurement Parameter