MACHINE LEARNING APPLICATION IN CARDIOLOGY: EMPLOYABILITY OF SUPPORT VECTOR MACHINE AND LOGISTIC REGRESSION IN THE EARLY STAGE DETECTION OF CARDIAC DISEASE
Raj Verma
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Abstract
A typical term heart disease is only a cardiovascular infection or a coronary illness which lessens the proficiency and legitimate working of heart by blocking veins, supply route or veins around it. Coronary illness causes handicap, for example, harm to the mind bringing about death. Given Statistics [10], it demonstrates that scope of age amass from 25 to 69 have 25% danger of having heart maladies. Some indispensable reasons for cardiovascular sickness are, physical idleness, smoking, expending more shoddy nourishment and dependence of liquor which are real foundations for stroke, chest agony, and heart assault. Anyway as a result of the mindfulness about components and indications that are in charge of the heart issue, it is conceivable to anticipate any heart issue dependent on a measurable examination of medical records. Anyway, Data mining, a cutting-edge strategy has given a programmed method for investigating information utilizing standard arrangement techniques. Although many classifiers are accessible in information mining that can be utilized to foresee the heart issues, this paper accentuates on finding the fitting classifier that can give better exactness by applying information mining systems viz: gullible Bayes, Support Vector machine and Logistic Regression.
Keywords: Coronary; Naive Bayes; Support Vector Machine; Logistic Regression
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