Language: English
Published by Cambridge University Press (edition 1), 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Hardcover. Condition: Good. 1. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
Language: English
Published by Cambridge University Press (edition 1), 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
Seller: BooksRun, Philadelphia, PA, U.S.A.
Hardcover. Condition: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Language: English
Published by Cambridge University Press CUP, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Published by Cambridge University Press
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hardcover. Condition: Good. Page/Cover Damage, A copy that may have been read, minimal to no highlighting/underlining of text, no missing pages. May have a remainder mark. Spine may show signs of wear. Could be a library copy.
Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Condition: As New. Unread book in perfect condition.
Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Language: English
Published by Cambridge University Press, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
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Hardcover. Condition: New. New. book.
Language: English
Published by Cambridge University Press, GB, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
£ 120.68
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Add to basketHardback. Condition: New. Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Gebunden. Condition: New. This accessible but rigorous introduction is written for advanced undergraduates and beginning graduate students in data science, as well as researchers and practitioners. It shows how a statistical framework yields sound estimation, testing and prediction .
Hardcover. Condition: Brand New. 427 pages. 10.00x7.00x1.00 inches. In Stock.
Language: English
Published by Cambridge University Press, GB, 2019
ISBN 10: 110849420X ISBN 13: 9781108494205
Seller: Rarewaves.com UK, London, United Kingdom
£ 110.97
Quantity: Over 20 available
Add to basketHardback. Condition: New. Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Hardcover. Condition: Brand New. 427 pages. 10.00x7.00x1.00 inches. In Stock. This item is printed on demand.