Least Absolute Shrinkage and Selection Operator

The Least Absolute Shrinkage and Selection Operator (LASSO) is a statistical method used for building predictive models, especially when dealing with many variables. It helps identify which variables truly matter by shrinking less important ones toward zero, effectively reducing their influence. This process simplifies the model, prevents overfitting, and can automatically select the most relevant variables. Think of it as fine-tuning a recipe to focus on the key ingredients, removing unnecessary ones to make the dish clearer and more effective.