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 language | English |
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Title of host publication | 2nd International Conference on Computer Science and Engineering, UBMK 2017 |
Publisher | IEEE |
Pages | 806-811 |
Number of pages | 6 |
ISBN (Electronic) | 9781538609309 |
ISBN (Print) | 9781538609316 |
DOIs | |
Publication status | Published - 31 Oct 2017 |
Externally published | Yes |
Event | 2nd International Conference on Computer Science and Engineering, UBMK 2017 - Antalya, Turkey Duration: 5 Oct 2017 → 8 Oct 2017 |
Conference/symposium
Conference/symposium | 2nd International Conference on Computer Science and Engineering, UBMK 2017 |
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Country/Territory | Turkey |
City | Antalya |
Period | 5/10/17 → 8/10/17 |
Keywords
- Clustering issues
- Clustering survey
- Taxonomy of clustering methods and model