Predicting the risk of heart disease using multiclass svm
M.Malini, V.Hima Bindu, P.Sabitha
Cite This Article:
Predicting the risk of heart disease using multiclass svmInternational Journal of Innovative Research in Technology( ,ISSN: 2349-6002 ,Volume 6 ,Issue 6 ,Page(s):62-65 ,November 2019 ,Available :IJIRT148757_PAPER.pdf
Heart disease, risk, Multiclass Support vector, machine learning
According to a survey conducted by India State-level Disease Burden Initiative in 1990 the deaths due to heart diseases was 15.2% whereas in 2016 the rate of deaths due to heart 28.1%. Heart disease is also the leading cause of death in India. Unhealthy diet, physical inactivity, smoking, alcohol consumption, stress and many more changes in our lifestyle has caused this increase in deaths due to heart disease. Age, gender and hereditary also cause people to have heart diseases. Predicting the risk of heart disease gives a clear view on treatment of the patients. In this paper we have proposed an efficient method to predict the risk rate of heart disease using the machine learning algorithm Multiclass support vector machine (MCSVM).
Article Details
Unique Paper ID: 148757

Publication Volume & Issue: Volume 6, Issue 6

Page(s): 62 - 65
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