CLUSTER ANALYSiS

[Continued...] Realistic data sets sometimes contain clusters within clusters. Partitional methods, as well as some hierarchical methods, are unable to detect subclusters. Density-based hierarchical clustering methods such as the single-link method and its relatives are well-suited to correctly identifying subclusters.

Sometimes care must be taken in selecting the best clustering method(s) for a particular dataset, and some experimentation may be required. Applying inappropriate methods to non-trivial data sets such as those described above can sometimes give undesirable or unexpected results:

(a) (b) (c)

Seventh Sense Software actively carries out research in-house into the development of state-of-the-art clustering algorithms and methods. For example we have developed the world's fastest single-link clustering algorithm for Euclidean datasets. Descriptions of some of our results and discoveries are available on the Algorithms page.