Comparison of linear regression with lasso regression for novel session time analysis using supply chain management in ordering ecommerce products on ecommerce data

The main objective of this research is to improve the accuracy of performing the novel session time analysis for various Ecommerce customer orders using supply chain management in ordering Ecommerce products using Linear Regression in comparison with Lasso Regression. Materials and Methods: Linear Regression algorithm with sample size=154 and Lasso Regression algorithm with sample size=154 with G power (value=0.8) were evaluated many times to forecast the accuracy percentage. Results: Linear Regression has better accuracy (85.62%) when compared to Lasso Regression (62.47%). The statistical significance difference (two-tailed) is 0.047 (p