CHIZIQLI REGRESSIYA MODELLARINING ANIQLIK DARAJASINI OSHIRISH USULLARI

Abstract

This paper provides a comprehensive analysis of methods for improving the accuracy of linear regression models. The study examines the effects of data preprocessing, multicollinearity, modern parameter estimation techniques, and regularization methods such as Ridge and Lasso on model accuracy. Experimental results indicate that the combined application of these approaches significantly enhances the predictive performance of linear regression models.