37. LASSO vs Linear Regression: Performance Comparison and Coefficient Analysis

Описание: 37. LASSO vs Linear Regression: Performance Comparison and Coefficient Analysis

In this section, we'll compare the performance of LASSO regression (with alpha=0.001) and standard linear regression on a holdout set. We'll examine how to properly implement both models with standardized features, including important considerations like increasing max_iterations for LASSO to ensure convergence. The discussion will cover how to evaluate model performance using R-squared scores and analyze coefficient magnitudes and sparsity. Through practical implementation, we'll see how LASSO not only achieves better prediction performance (0.868 vs 0.855 R-squared) but also produces more parsimonious models with significantly smaller coefficient magnitudes (436 vs 1,185) and fewer non-zero coefficients. This comparison demonstrates the benefits of regularization in both model performance and interpretability.