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Finding Groups in Data: An Introduction to Cluster Analysis by Leonard Kaufman, Peter J. Rousseeuw

Finding Groups in Data: An Introduction to Cluster Analysis Leonard Kaufman, Peter J. Rousseeuw ebook
Page: 355
Format: pdf
Publisher: Wiley-Interscience
ISBN: 0471735787, 9780471735786

The identification of the cluster centroid or the most representative [voucher or barcode] .. The Wiley–Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability 1967, 1:281-297. The exponential accumulation of DNA and protein sequencing data has demanded efficient tools for the comparison, analysis, clustering, and classification of novel and annotated sequences [1,2]. Instructors can also use it as a textbook for an introductory course in cluster analysis or as source material for a graduate-level introduction to data mining. Kaufman L, Rousseeuw PJ: Finding groups in data: an introduction to cluster analysis. Kaufman L, Rousseeuw P: Finding Groups in Data: An Introduction to Cluster Analysis. SIAM J Comput 1982, 11(4):721-736. ACM San Francisco Bay Area Professional Chapter course. Audience The following groups will find this book a valuable tool and reference: applied statisticians; engineers and scientists using data analysis; researchers in pattern recognition, artificial intelligence, machine learning, and data mining; and applied mathematicians. Hoboken, New Jersey: Wiley; 2005. This course outline includes R introduction (including getting unstuck), Data Management, Graphics, and Statistical Analysis and Data Mining. Finding groups in data: An introduction to cluster analysis. The grouping process implements a clustering methodology called "Partitioning Around Mediods" as detailed in chapter 2 of L.