Ordinal Classification

Ordinal Classification is a machine learning task that aims to assign data to categories with a natural order. Its goal is not only to predict the category labels but also to maintain the order consistency among these labels. By introducing ordinal information, this method can more accurately reflect the hierarchical structure in the real world, thereby enhancing the rationality and interpretability of predictions. Ordinal Classification has significant application value in areas such as sentiment analysis, credit rating, and medical diagnosis, effectively supporting decision-making and risk assessment.