TY  - JOUR
T1  - Improvement of Ridge Regression Using Differential Evolution
AU - , Sung-Hae Jun AU - , Im-Geol Oh 
JO  - Journal of Engineering and Applied Sciences
VL  - 2
IS  - 10
SP  - 1509
EP  - 1515
PY  - 2007
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2007.1509.1515
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2007.1509.1515
KW  - Improvement
KW  -ride regression
KW  -differential evolution
KW  -regression model
AB  - Multicollinearity problem in learning machines occurs when there are high dependencies among the input variables. The problem increases the variance of predictive model to cause unstable results. In regression models, the multicollinearity is also a problem to be solved. Ridge regression is a good method to settle the problem of regression. In general, the shrinkage parameter of ridge regression is determined by the arts of researchers. But, the selections are not always good. So, in this study, we propose an improvement of ridge regression using differential evolution. This is an evolutionary ridge regression to find better shrinkage parameter. To verify performance of our research, we make experiments using objective data sets.
ER  -