dlordinal is a new Python library that unifies many recent deep ordinal classification methodologies available in the literature. Developed using PyTorch as underlying framework, it implements the top performing state-of-the-art deep learning techniques for ordinal classification problems. Ordinal approaches are designed to leverage the ordering information present in the target variable. Specifically, it includes loss functions, various output layers, dropout techniques, soft labelling methodologies, and other classification strategies, all of which are appropriately designed to incorporate the ordinal information. Furthermore, as the performance metrics to assess novel proposals in ordinal classification depend on the distance between target and predicted classes in the ordinal scale, suitable ordinal evaluation metrics are also included. dlordinal is distributed under the BSD-3-Clause license and is available at https://github.com/ayrna/dlordinal.

翻译：dlordinal是一个新的Python库，它统一了文献中许多最新的深度序数分类方法。该库使用PyTorch作为底层框架开发，实现了针对序数分类问题性能最优的先进深度学习技术。序数方法旨在利用目标变量中存在的排序信息。具体而言，它包含了损失函数、多种输出层、dropout技术、软标签方法以及其他分类策略，所有这些都经过专门设计以融入序数信息。此外，由于评估序数分类中新提案的性能指标取决于序数尺度上目标类别与预测类别之间的距离，因此该库还包含了合适的序数评估指标。dlordinal采用BSD-3-Clause许可证分发，可通过https://github.com/ayrna/dlordinal获取。