CAJ | 학술논문

研究 Logistic回归模型的主成分回归改进方法。在医学研究中，尤其是在流行病的发病因素分析中，应用主成分回归进行多重共线性的改进处理，可以削减自变量观察矩阵之间的多重共线性，建立较为理想的关系模型，提高结果的可靠性；便于医学研究者正确合理的建立Logistic回归模型，处理混杂因素，预测疾病和判别分类。
연구 Logistic회귀모형적주성분회귀개진방법。재의학연구중，우기시재류행병적발병인소분석중，응용주성분회귀진행다중공선성적개진처리，가이삭감자변량관찰구진지간적다중공선성，건립교위이상적관계모형，제고결과적가고성；편우의학연구자정학합리적건립Logistic회귀모형，처리혼잡인소，예측질병화판별분류。
This article mainly studies the enhancing methods of the principal component of Logistic Re-gression .In medical research ,especially in the analyses of the aetiological agents of opidemics ,the applica-tion of principal component regression to the improvements of multi-collinearity can reduce the multi-col-linearity between matrices of variables ,build up relatively ideal relation models and improve the reliability of results .Meanwhile ,it enables medical researchers to establish rational Logistic Regression models ,deal with thorny problems ,predict diseases and classify them .