Dark patches in clustering

Waqar Ishaq, Eliya Buyukkaya

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

1 Citation (Scopus)

Abstract

This survey highlights issues in clustering which hinder in achieving optimal solution or generates inconsistent outputs. We called such malignancies as dark patches. We focus on the issues relating to clustering rather than concepts and techniques of clustering. For better insight into the issues of clustering, we categorize dark patches into three classes and then compare various clustering methods to analyze distributed datasets with respect to classes of dark patches rather than conventional way of comparison by performance and accuracy criteria, because performance and accuracy may provide misleading conclusions due to lack of labeled data in unsupervised learning. To the best of our knowledge, this prime feature makes our survey paper unique from other clustering survey papers.

Original languageEnglish
Title of host publication2nd International Conference on Computer Science and Engineering, UBMK 2017
PublisherIEEE
Pages806-811
Number of pages6
ISBN (Electronic)9781538609309
ISBN (Print)9781538609316
DOIs
Publication statusPublished - 31 Oct 2017
Externally publishedYes
Event2nd International Conference on Computer Science and Engineering, UBMK 2017 - Antalya, Turkey
Duration: 5 Oct 20178 Oct 2017

Conference/symposium

Conference/symposium2nd International Conference on Computer Science and Engineering, UBMK 2017
Country/TerritoryTurkey
CityAntalya
Period5/10/178/10/17

Keywords

  • Clustering issues
  • Clustering survey
  • Taxonomy of clustering methods and model

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