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Cluster Analysis as a Decision-Making Tool

Cluster Analysis as a Decision-Making Tool

Bindu Rani, Shri Kant
Copyright: © 2023 |Pages: 28
ISBN13: 9781799892205|ISBN10: 1799892204|EISBN13: 9781799892212
DOI: 10.4018/978-1-7998-9220-5.ch024
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MLA

Rani, Bindu, and Shri Kant. "Cluster Analysis as a Decision-Making Tool." Encyclopedia of Data Science and Machine Learning, edited by John Wang, IGI Global, 2023, pp. 382-409. https://doi.org/10.4018/978-1-7998-9220-5.ch024

APA

Rani, B. & Kant, S. (2023). Cluster Analysis as a Decision-Making Tool. In J. Wang (Ed.), Encyclopedia of Data Science and Machine Learning (pp. 382-409). IGI Global. https://doi.org/10.4018/978-1-7998-9220-5.ch024

Chicago

Rani, Bindu, and Shri Kant. "Cluster Analysis as a Decision-Making Tool." In Encyclopedia of Data Science and Machine Learning, edited by John Wang, 382-409. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-7998-9220-5.ch024

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Abstract

Despite an increase in big data analytics research, many challenges still exist in designing the methodologies for enhancing big data analytical technologies towards achieving more informed decisions. This chapter addresses the frameworks to support the decision-making process by combining big data analytical techniques and decision theory. With the breakthrough of big data characteristics progressively, several new challenges appear. Clustering as an important tool has the capacity to support decision making processes. Consequently, this article explores the behaviour of different clustering methods and their algorithm approaches. The main gravity is to concentrate on the role of various cluster validity indices and their core principles to identify arrangements of patterns and interesting correlation in big data.

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