Performance evaluation of some clustering algorithms and validity indices
Abstract
In this article, we evaluate the performance of three clustering algorithms, hard K-Means, single linkage, and a simulated annealing (SA) based technique, in conjunction with four cluster validity indices, namely Davies-Bouldin index, Dunn's index, Calinski-Harabasz index, and a recently developed index I. Based on a relation between the index I and the Dunn's index, a lower bound of the value of the former is theoretically estimated in order to get unique hard K-partition when the data set has distinct substructures. The effectiveness of the different validity indices and clustering methods in automatically evolving the appropriate number of clusters is demonstrated experimentally for both artificial and real-life data sets with the number of clusters varying from two to ten. Once the appropriate number of clusters is determined, the SA-based clustering technique is used for proper partitioning of the data into the said number of clusters.
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BiasWatch is a recently-proposed, light-weight approach to compute controversy scores for users on Twitter.
“BiasWatch [37] is a recently-proposed, light-weight approach to compute controversy scores for users on Twitter.”
From Quantifying controversy on social media (2018) · cites this paper as [37]
The authors of [37] provide datasets containing human annotations for controversy score (range [-2,2]) for 500 randomly selected users.
“The authors also provide datasets which contain human annotations for controversy score (in the range [-2,2]) for 500 randomly selected users.”
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- Authors
- Maulik, U., & Bandyopadhyay, S.
- Affiliations
- The University of Texas at Arlington (US)
- Indian Statistical Institute (IN)
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2002-12
- Volume
- 24
- Issue
- 12
- Pages
- 1650-1654
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2108323654
- Cited by
- 1,396
- References
- 0
- Citations by year
- 2026: 36 · 2025: 65 · 2024: 85 · 2023: 53 · 2022: 78 · 2021: 89 · 2020: 105 · 2019: 87 · 2018: 110 · 2017: 55 · 2016: 68 · 2015: 56 · 2014: 62 · 2013: 49 · 2012: 57
- FWCI
- 13.85
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Pattern Analysis and Machine Intelligence (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Clustering Algorithms Research
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
- Keywords
- clustering algorithms, cluster validity indices, K-means clustering, single linkage, simulated annealing, Davies-Bouldin index, Dunn index, Calinski-Harabasz index, automatic cluster number selection
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