Example Concept: One effective method for feature selection in linear regression is using LASSO (Least Absolute Shrinkage and Selection Operator) regression. LASSO adds a penalty equal to the absolute value of the magnitude of coefficients, which can shrink some coefficients to zero, effectively selecting a simpler model with fewer features. This method is particularly useful when dealing with datasets with a large number of features, as it helps in identifying the most impactful variables while reducing overfitting.