A Decision Model for Fuzzy Clustering Ensemble
- 10.2991/iske.2007.210How to use a DOI?
- Fuzzy Clustering Ensemble,
Recent research and experiments have showed that clustering ensemble approaches can enhance the robustness and stabilities of unsupervised learning greatly. Most of them focused on crisp clustering combination. However, in this paper, we offer a decision model based on fuzzy set theory for fuzzy clustering ensemble. Firstly, obtain the optimal partition called “expert” from H individual fuzzy partitions generated by fuzzy c-means algorithm. Then, use fuzzy voting scheme to generate the majority judger. Finally, the two matrixes are combined by Decision Model. Experimental results show the effectiveness of the proposed method comparing to the results based on crisp clustering.
- © 2007, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yanqiu Fu AU - Yan Yang PY - 2007/10 DA - 2007/10 TI - A Decision Model for Fuzzy Clustering Ensemble BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 1236 EP - 1241 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.210 DO - 10.2991/iske.2007.210 ID - Fu2007/10 ER -