Prediction intervals aim to contain future individual observations, while confidence intervals target a mean or other parameter, and the two are not interchangeable. Empirical coverage is the held-out fraction inside the interval and width is the distance between quantile limits; a constructed five-value example gives 80 percent coverage and mean width 1.8.
prediction interval / confidence interval / quantile regression / empirical coverage / interval width / scikit-learn / calibration / held-out evaluation
Read training and validation scores together, fit preprocessing inside a pipeline and keep a final test set out of model selection.
Machine Learning / Validation / Overfitting
Build a previous-season reference, evaluate it on later observations and distinguish calendar alignment from leakage and missing data.
Time Series / Forecasting / Baseline / Validation