Machine Learning, Gradient Boosting, Data Science, Towards Data Science, Loss Function.
density plot of the residuals. Comparison of predictions from LightGBM models with symmetric and asymmetric evaluation Conclusion All models have error, but many business problems do not treat underestimates and overestimates equally. Sometimes, we intentionally want our model to bias our errors in