Neighborgram Clustering Interactive Exploration of Cluster Neighborhoods

Proceedings of IEEE Data Mining, IEEE Press, pp. 581-584, 2002. We describe an interactive way to generate a set of clusters for a given data set. The clustering is done by constructing local histograms, which can then be used to visualize, select, and fine-tune potential cluster candidates. The accompanying algorithm can also generate clusters automatically, allowing for an automatic or semi-automatic clustering process where the user only occasionally interacts with the algorithm. We illustrate the ability to automatically identify and visualize clusters using NCI’s AIDS Antiviral Screen data set.

• Type: Conference
• Year: 2002
• Where: ICDM
• Authors: Michael R. Berthold, Bernd Wiswedel, David E. Patterson
• Keywords: Data Mining, Data Set, ICDM 2002, IEEE Data Mining, Semi-automatic Clustering Process