استعمال خوارزمية تجزئة القيم المفردة لمعالجة مشكلة التعدد الخطي (عالية الإبعاد)‎ لتحديد و تميز أهم العوامل المؤثرة على إمراض القلب

Abstract EN

In this paper, one of the problems of statistical data was examined in the case of multicollinearity variables.

This is the problem of linear multicollinearity.

The problem multicollinearity was solved using a Singular Value Decomposition that changes the structure of the data to eliminate the problem while preserving the nature of the data in terms of the effect on the variable Affiliate.

Comparative analysis and logistic analysis were used to compare the two after the application of a single value fragmentation algorithm to medical data representing recovery status and death of heart attack (y = 0 deaths, y = 1 healing) and factors affecting heart attack After the differential analysis, the most important factors with a high effect on heart attack were (emotion, heart disease, smoking, age).

In the case of logistic analysis (emotion, heart disease, smoking, pressure, sugar and age) Affect the heart attack disease.