Dark Patches in Clustering
Loading...
Date
2017
Authors
Ishaq, Waqar
Büyükkaya, Eliya
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
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.
Description
Keywords
Clustering issues, Taxonomy of clustering methods and model, Clustering survey
Turkish CoHE Thesis Center URL
Citation
1
WoS Q
N/A
Scopus Q
N/A
Source
Volume
Issue
Start Page
806
End Page
811