Effective Amazon Machine Learning

Choosing regularization

As seen in Chapter 2, Machine Learning Definitions and Concepts, regularization makes your model more robust and allows it to better handle previously unseen data by reducing overfitting. The rule of thumb is to lower regularization if your evaluation score is poor (underfitting) and increase it if your model shows great performance on the training set but poor results on the evaluation set (overfitting).