+Lasso Regression is a [Machine Learning](/wiki/machine_learning) technique designed to enhance the accuracy and interpretability of statistical models. It imposes an L1 penalty, shrinking less important coefficients to zero, thereby performing [Feature Selection](/wiki/feature_selection) and yielding simpler, more robust models. This method elegantly balances model fit with parsimony.
+## See also
+- [Ridge Regression](/wiki/ridge_regression)
+- [Linear Regression](/wiki/linear_regression)
+- [Regularization](/wiki/regularization)
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