Ordinal imbalanced datasets are pervasive in real world applications but remain challenging to analyse as they require specific methods to account for the ordering information and imbalanced classes. Failure to account for both those characteristics can substantially impact the model predictive performance. However. existing methods tend to focus either on ordinality or imbalance. https://danddcollectiblers.shop/product-category/easter-table-decor/