Concept Formation in Complex Domains
Abstract
Most empirical learning algorithms describe objects as a list of attribute-value pairs. A flat attribute-value representation fails, however, to capture the internal structure of real objects. Mechanisms are therefore needed to represent the different levels of detail at which an object can be seen. A common structuring method is reviewed, and new principles of evaluation are proposed. As another way of enriching the representation language, a formalism is also proposed for multi-valued attributes, allowing the representation of sets of objects.
Cite
Text
Ketterlin and Korczak. "Concept Formation in Complex Domains." European Conference on Machine Learning, 1994. doi:10.1007/3-540-57868-4_76Markdown
[Ketterlin and Korczak. "Concept Formation in Complex Domains." European Conference on Machine Learning, 1994.](https://mlanthology.org/ecmlpkdd/1994/ketterlin1994ecml-concept/) doi:10.1007/3-540-57868-4_76BibTeX
@inproceedings{ketterlin1994ecml-concept,
title = {{Concept Formation in Complex Domains}},
author = {Ketterlin, Alain and Korczak, Jerzy J.},
booktitle = {European Conference on Machine Learning},
year = {1994},
pages = {371-374},
doi = {10.1007/3-540-57868-4_76},
url = {https://mlanthology.org/ecmlpkdd/1994/ketterlin1994ecml-concept/}
}