Machine Learning, Gradient Boosting, Data Science, Towards Data Science, Loss Function.
find the gradient and hessian. As we’ll see next, often it is easier to first change the validation loss, as it doesn’t require as much overhead. Validation loss The validation loss is used to tune hyper-parameters. It is often easier to customize, as it doesn’t have as many functional requirements