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All Journal Operations Research: International Conference Series
Bastiaan, Richy Marcelino
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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Comparing the Performance of Prediction Model of Ridge and Elastic Net in Correlated Dataset Bastiaan, Richy Marcelino; Salaki, Deiby Tineke; Hatidja, Djoni
Operations Research: International Conference Series Vol. 3 No. 1 (2022): Operations Research International Conference Series (ORICS), March 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i1.127

Abstract

Multicollinearity refers to a condition where high correlation between independent variables in linear regression model occurs.  In this case, using ordinary least squares (OLS) leads to unstable model. Some penalized regression approaches such as ridge and elastic-net regression can be applied to overcome the problem. Penalized regression estimates model by adding a constrain on the size of parameter regression. In this study, simulation dataset is generated, comprised of 100 observation and 95 independent variables with high correlation. This empirical study shows that elastic-net method outperforms the ridge regression and OLS.  In correlated dataset, the OLS is failed to produce a prediction model based on mean squared error (MSE)
Co-Authors Deiby T Salaki Djoni Hatidja