Abstract
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.
Cite
CITATION STYLE
Nayak, S., Kumar Gourisaria, M., Pandey, M., & Swarup Rautaray, S. (2019). Heart Disease Prediction Using Frequent Item Set Mining and Classification Technique. International Journal of Information Engineering and Electronic Business, 11(6), 9–15. https://doi.org/10.5815/ijieeb.2019.06.02
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.