Clustering breast cancer data by consensus of different validity indices

D. Soria, J. M. Garibaldi, F. Ambrogi, P. J G Lisboa, P. Boracchi, E. Biganzoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Clustering algorithms will, in general, either partition a given data set into a pre-specified number of clusters or will produce a hierarchy of clusters. In this paper we analyse several different clustering techniques and apply them to a particular data set of breast cancer data. When we do not know a priori which is the best number of groups, we use a range of different validity indices to test the quality of clustering results and to determine the best number of clusters. While for the K-means method there is not absolute agreement among the indices as to which is the best number of clusters, for the PAM algorithm all the indices indicate 4 as the best cluster number.

Original languageEnglish
Title of host publicationIET Conference Publications
Edition540 CP
DOIs
Publication statusPublished - 2008
Event4th IET International Conference on Advances in Medical, Signal and Information Processing, MEDSIP 2008 - Santa Margherita Ligure, Italy
Duration: Jul 14 2008Jul 16 2008

Other

Other4th IET International Conference on Advances in Medical, Signal and Information Processing, MEDSIP 2008
CountryItaly
CitySanta Margherita Ligure
Period7/14/087/16/08

Fingerprint

Pulse amplitude modulation
Clustering algorithms

Keywords

  • Breast cancer
  • Clustering algorithms
  • Validity indices

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Soria, D., Garibaldi, J. M., Ambrogi, F., Lisboa, P. J. G., Boracchi, P., & Biganzoli, E. (2008). Clustering breast cancer data by consensus of different validity indices. In IET Conference Publications (540 CP ed.) https://doi.org/10.1049/cp:20080437

Clustering breast cancer data by consensus of different validity indices. / Soria, D.; Garibaldi, J. M.; Ambrogi, F.; Lisboa, P. J G; Boracchi, P.; Biganzoli, E.

IET Conference Publications. 540 CP. ed. 2008.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Soria, D, Garibaldi, JM, Ambrogi, F, Lisboa, PJG, Boracchi, P & Biganzoli, E 2008, Clustering breast cancer data by consensus of different validity indices. in IET Conference Publications. 540 CP edn, 4th IET International Conference on Advances in Medical, Signal and Information Processing, MEDSIP 2008, Santa Margherita Ligure, Italy, 7/14/08. https://doi.org/10.1049/cp:20080437
Soria D, Garibaldi JM, Ambrogi F, Lisboa PJG, Boracchi P, Biganzoli E. Clustering breast cancer data by consensus of different validity indices. In IET Conference Publications. 540 CP ed. 2008 https://doi.org/10.1049/cp:20080437
Soria, D. ; Garibaldi, J. M. ; Ambrogi, F. ; Lisboa, P. J G ; Boracchi, P. ; Biganzoli, E. / Clustering breast cancer data by consensus of different validity indices. IET Conference Publications. 540 CP. ed. 2008.
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