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CiteWeb id: 20090000012

CiteWeb score: 10504

Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organising multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques are applicable in a wide range of areas such as medicine, psychology and market research. This fourth edition of the highly successful Cluster Analysis represents a thorough revision of the third edition and covers new and developing areas such as classification likelihood and neural networks for clustering. Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. The book is comprehensive yet relatively non-mathematical, focusing on the practical aspects of cluster analysis.

The publication "Cluster Analysis" is placed in the Top 1000 of the best publications in CiteWeb. Also in the category Computer Science it is included to the Top 1000. Additionally, the publicaiton "Cluster Analysis" is placed in the Top 100 among other scientific works published in 2009.
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