Ordered Classes and Incomplete Examples in Classification
Abstract
The classes in classification tasks often have a natural ordering, and the training and testing examples are often incomplete. We propose a non(cid:173) linear ordinal model for classification into ordered classes. Predictive, simulation-based approaches are used to learn from past and classify fu(cid:173) ture incomplete examples. These techniques are illustrated by making prognoses for patients who have suffered severe head injuries.
Cite
Text
Mathieson. "Ordered Classes and Incomplete Examples in Classification." Neural Information Processing Systems, 1996.Markdown
[Mathieson. "Ordered Classes and Incomplete Examples in Classification." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/mathieson1996neurips-ordered/)BibTeX
@inproceedings{mathieson1996neurips-ordered,
title = {{Ordered Classes and Incomplete Examples in Classification}},
author = {Mathieson, Mark},
booktitle = {Neural Information Processing Systems},
year = {1996},
pages = {550-556},
url = {https://mlanthology.org/neurips/1996/mathieson1996neurips-ordered/}
}