Lasso Regression, Regression, Machine Learning, Data Science, Regularization.
regularization parameter. The goal is to minimize this cost function by adjusting the coefficients of the model. The lasso regression has the added benefit of feature selection, as it tends to shrink the coefficient of less important features to zero, effectively eliminating them from the model.