Abstract
Clustering is the process of grouping a set of physical or abstract objects into classes of similar objects. A cluster is a collection of data objects that are similar to one another within the same cluster and are dissimilar to the objects in other clusters. Although classication is an effective means for distinguishing groups or classes of objects, it often requires costly collection and labeling of a large set of training tuples or patterns, which the classier uses to model each group. In contrast, clustering does not require such labeling at all.
| Original language | English (US) |
|---|---|
| Title of host publication | Geographic Data Mining and Knowledge Discovery, Second Edition |
| Publisher | CRC Press |
| Pages | 149-188 |
| Number of pages | 40 |
| ISBN (Electronic) | 9781420073980 |
| ISBN (Print) | 9781420073973 |
| DOIs | |
| State | Published - Jan 1 2009 |
ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)
- Earth and Planetary Sciences(all)
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Han, J., Lee, J. G., & Kamber, M. (2009). An overview of clustering methods in geographic data analysis. In Geographic Data Mining and Knowledge Discovery, Second Edition (pp. 149-188). CRC Press. https://doi.org/10.1201/9781420073980