Abstract
Many real-world and man-made objects are symmetry, therefore, it is reasonable to assume that some kind of symmetry may exist in data clusters. In this paper a new cluster validity measure which adopts a non-metric distance measure based on the idea of "line symmetry" is presented. The proposed validity measure can be applied in finding the number of clusters of different geometrical structures. Several data sets are used to illustrate the performance of the proposed measure.
| Original language | English |
|---|---|
| Pages (from-to) | 443-461 |
| Number of pages | 19 |
| Journal | Journal of Information Science and Engineering |
| Volume | 30 |
| Issue number | 2 |
| State | Published - Mar 2014 |
Keywords
- Cluster analysis
- Cluster validity
- Clustering algorithm
- Line symmetry
- Similarity measure
- Unsupervised learning