Applications of monitoring and tracing the evolution of clustering solutions in dynamic datasets-Reference-Cited by-同舟云学术

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Applications of monitoring and tracing the evolution of clustering solutions in dynamic datasets

Published:2021-12-07 Issue: Volume: Page:1-19
ISSN:0266-4763
Container-title:Journal of Applied Statistics
language:en
Short-container-title:Journal of Applied Statistics

Author:

Atif Muhammad¹,Shafiq Muhammad²,Leisch Friedrich³

Affiliation:

1. Department of Statistics, University of Peshawar, Peshawar, Pakistan

2. Institute of Numerical Sciences, Kohat University of Science and Technology, Kohat, Pakistan

3. Institute of Statistics, University of Natural Resources and Life Sciences, Vienna, Austria

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/02664763.2021.2008882

Reference45 articles.

1. S. Badiozamany, K. Orsborn, and T. Risch, Framework for Real-Time Clustering Over Sliding Windows, Proceedings of the 28th International Conference on Scientific and Statistical Database Management – SSDBM 16, Association for Computing Machinery, New York, NY, 2016. doi:10.1145/2949689.2949696.

2. Partitional Clustering via Nonsmooth Optimization

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1. The least sample size essential for detecting changes in clustering solutions of streaming datasets;PLOS ONE;2024-02-20

2. Evolution of waterborne diseases: A case study of Khyber Pakhtunkhwa, Pakistan;SAGE Open Medicine;2024-01

3. Monitoring Changes in Clustering Solutions: A Review of Models and Applications;Journal of Probability and Statistics;2023-11-03

4. clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets;PLOS ONE;2022-12-15

5. Evolution of basic human values orientations: An application of monitoring changes in cluster solutions;PLOS ONE;2022-09-30

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