A New Way to Predict Probability Distributions
Exploring multi-quantile regression with Catboost
Harrison Hoffman
Feb 14
“Until recently, the main disadvantage of quantile regression was that one model had to be trained per predicted quantile…. Catboost has since addressed this issue with the multi-quantile loss function — a loss function that enables a single model to predict an arbitrary number of quantiles.”