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Clustering Analysis and Algorithms

Clustering Analysis and Algorithms

Xiangji Huang
Copyright: © 2008 |Pages: 8
ISBN13: 9781599049410|ISBN10: 1599049414|EISBN13: 9781599049427
DOI: 10.4018/978-1-59904-941-0.ch021
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MLA

Huang, Xiangji. "Clustering Analysis and Algorithms." Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications, edited by Vijayan Sugumaran, IGI Global, 2008, pp. 389-396. https://doi.org/10.4018/978-1-59904-941-0.ch021

APA

Huang, X. (2008). Clustering Analysis and Algorithms. In V. Sugumaran (Ed.), Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications (pp. 389-396). IGI Global. https://doi.org/10.4018/978-1-59904-941-0.ch021

Chicago

Huang, Xiangji. "Clustering Analysis and Algorithms." In Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications, edited by Vijayan Sugumaran, 389-396. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-941-0.ch021

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Abstract

Clustering is the process of grouping a collection of objects (usually represented as points in a multidimensional space) into classes of similar objects. Cluster analysis is a very important tool in data analysis. It is a set of methodologies for automatic classification of a collection of patterns into clusters based on similarity. Intuitively, patterns within the same cluster are more similar to each other than patterns belonging to a different cluster. It is important to understand the difference between clustering (unsupervised classification) and supervised classification.

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