A Constrained Cluster Ensemble Using Hierarchical Clustering Methods
Allbwn ymchwil: Cyfraniad at gynhadledd › Papur › adolygiad gan gymheiriaid
Fersiynau electronig
Dangosydd eitem ddigidol (DOI)
Unsupervised classification of data is an ongoing challenge in many areas. With evolving stream data, hierar-chical clustering methods have proved effective, especially with non-spherical clusters. Additionally, incorporating pairwise con-straints has been shown to further improve clustering accuracy. We propose a cluster ensemble using constrained hierarchical methods. The experiment was performed on a collection of 52 Synthetic and 96 Real datasets. Our analysis shows that our constrained cluster ensemble method results in a high accuracy across various proportions of constraints without sacrificing speed
| Iaith wreiddiol | Saesneg |
|---|---|
| Dynodwyr Gwrthrych Digidol (DOIs) | |
| Statws | Cyhoeddwyd - Awst 2024 |
| Digwyddiad | 2024 IEEE 12th International Conference on Intelligent Systems (IS) - Varna, Bwlgaria Hyd: 29 Awst 2024 → 31 Awst 2024 http://10.1109/IS61756.2024.10705267 |
Cynhadledd
| Cynhadledd | 2024 IEEE 12th International Conference on Intelligent Systems (IS) |
|---|---|
| Gwlad/Tiriogaeth | Bwlgaria |
| Dinas | Varna |
| Cyfnod | 29/08/24 → 31/08/24 |
| Cyfeiriad rhyngrwyd |