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Research Article

JCR. 2020; 7(14): 1712-1720


Ramkumar P,Thanusha K,Soumya U,Sahana K,Sushma M.

Cardiovascular disease is one of the most important fatality of death in today world. Heart disease prediction is a serious issue in the field of medical data analysis. A method is proposed that aims at identifying major features by applying machine learning techniques resulting in increasing the accuracy in the prediction of heart disease. Scientists have been utilizing a few machine learning methods to assist wellbeing with caring experts in the conclusion of coronary illness. The World Health Organization (WHO) insight gives data that the cardio vascular ailments have a tremendous arrangement of enthusiasm for clinical research attributable to its effect on individual wellbeing. This will produce an enhanced performance level with an higher accuracy level through the prediction model for heart disease using Hybrid algorithm. This module introduces with various features of combinations and many specified classification techniques. Therefore, this makes use of hybrid random forest with a linear model (HRFLM).

Key words: Machine learning(ml) techniques, prediction model, hybrid algorithm, hybrid random forest with linear model (HRFLM),Cardiovascular Disease

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