Ridge Regression

Ridge Regression is a statistical method used to improve the accuracy of predicting outcomes when you have many related variables. It works by adding a slight penalty to the complexity of the model, discouraging it from relying too heavily on any single variable. This helps prevent overfitting, where a model performs well on existing data but poorly on new data. Essentially, Ridge Regression balances fitting the data accurately and keeping the model simple, leading to more reliable predictions, especially when the predictors are highly correlated or numerous.