Feature Request: Ordinal Classification [wish list]

[hrbzkm98]

Similar to #695 (closed). In the original discussion, participants did not seem to understand the difference between "learning-to-rank" and "ordinal classification". "learning-to-rank" produce relative ordering between items, and the output predictions are not class labels, while "ordinal classification" does produce class labels. Here is a blog post to introduce the reader to loss functions for ordinal classification.

Would certainly wish to have developers collaborate on this project of mine to integrate XGBoost with Ordinal Classification. However, the tricky part is the additional parameter "theta" (vector of thresholds) has to be optimized, before one can calculate the optimal leaf weight w. Currently XGBoost does not have support for custom loss function with additional custom parameters.

If you are curious, here is the brief introduction to ordinal classification introduction and its loss function that I wrote.