Title: cluster analysis
Long Title: IUPAC Gold Book - cluster analysis
DOI: 10.1351/goldbook.CT06950
Status: current

Definition
Cluster analysis is the clustering, or grouping, of large data sets (e.g., chemical and/or pharmacological data sets) on the basis of similarity criteria for appropriately scaled variables that represent the data of interest. Similarity criteria (distance based, associative, correlative, probabilistic) among the several clusters facilitate the recognition of patterns and reveal otherwise hidden structures.

Related Term
- Cluster: https://goldbook.iupac.org/terms/view/CT06769

Source
- PAC, 1997, 69, 1137. 'Glossary of terms used in computational drug design (IUPAC Recommendations 1997)' on page 1140 (https://doi.org/10.1351/pac199769051137)

Other Outputs
- html: https://goldbook.iupac.org/terms/view/CT06950/html
- json: https://goldbook.iupac.org/terms/view/CT06950/json
- xml: https://goldbook.iupac.org/terms/view/CT06950/xml

Citation: Citation: 'cluster analysis' in IUPAC Compendium of Chemical Terminology, 5th ed. International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.CT06950
License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International (https://creativecommons.org/licenses/by-sa/4.0/) for individual terms.
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Disclaimer: The International Union of Pure and Applied Chemistry (IUPAC) is continuously reviewing and, where needed, updating terms in the Compendium of Chemical Terminology (the IUPAC Gold Book). Users of these terms are encouraged to include the version of a term with its use and to check regularly for updates to term definitions that you are using.
Accessed: 2026-05-10T02:26:54+00:00