A fully autonomous Data Density based Clustering technique

Richard Hyde, Plamen Angelov

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

7 Citations (Scopus)


A recently introduced data density based approach to clustering, known as Data Density based Clustering has been presented which automatically determines the number of clusters. By using the Recursive Density Estimation for each point the number of calculations is significantly reduced in offline mode and, further, the method is suitable for online use. The Data Density based Clustering method however requires an initial cluster radius to be entered.

Original languageEnglish
Title of host publicationIEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - EALS 2014
Subtitle of host publication2014 IEEE Symposium on Evolving and Autonomous Learning Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781479944958, 9781479944941
Publication statusPublished - 15 Jan 2015
Externally publishedYes
Event2014 IEEE Symposium on Evolving and Autonomous Learning Systems - Orlando, United States
Duration: 9 Dec 201412 Dec 2014


Conference2014 IEEE Symposium on Evolving and Autonomous Learning Systems
Abbreviated titleEALS 2014
Country/TerritoryUnited States
Internet address


  • Automated clustering
  • Autonomous clustering
  • Data density
  • RDE
  • Recursive density estimation

ASJC Scopus subject areas

  • Artificial Intelligence

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