심장질환 및 당뇨병의 재발 위험요인의 예측을 위한 SVM 기반 회귀분석의 성능비교

Comparison of the SVM-based Regression Analysis for Prediction of Recurrence Risk Factors of Heart disease and diabetes

Recently, as the Korean Digital equipment and technology develops, by analyzing the stored data, in order to provide my users know the new information, data mining techniques have been utilized. Data mining techniques are verified according to the purpose to be used, confirmation, discovered, are used for purposes such as prediction. In this paper, not only patients with no cardiovascular or coronary artery disease is blood sugar valued dye in the risk factors that provided, blood pressure, aspirin, to evaluate the risk of heart disease and diabetes to have a non smoking, and to predict the risk, that give us the user is desired, using a regression analysis. Regression analysis, are suitable for predictive analytics, you will be able to perform a variety of regression analysis. Typically there is an SVM-based regression analysis. SVM is analysis capability for performing error generalized in a direction to a minimum is evaluated as excellent. By analyzing the SVM-based regression and general multiple regression analysis to compare the performance SVM.