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Recent advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Hence clustering and classification techniques that were once predominantly the domain of ecologists are now being used more widely. This book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques. It aims to provide a framework that will enable the reader to recognise the assumptions and constraints that are implicit in all such techniques. Important generic issues are discussed first and then the major families of algorithms are described. Throughout the focus is on explanation and understanding and readers are directed to other resources that provide additional mathematical rigour when it is required. Examples taken from across the whole of biology, including bioinformatics, are provided throughout the book to illustrate the key concepts and each technique's potential.
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1
Cluster and Classification Techniques for the Biosciences
2010, Cambridge University Press
in English
0511607490 9780511607493
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2
Cluster and Classification Techniques for the Biosciences
January 15, 2007, Cambridge University Press
Hardcover
in English
- 1 edition
0521852811 9780521852814
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3
Cluster and Classification Techniques for the Biosciences
January 15, 2007, Cambridge University Press
Paperback
in English
- 1 edition
0521618002 9780521618007
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4
Cluster and Classification Techniques for the Biosciences
2006, Cambridge University Press
in English
0511260024 9780511260025
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5
Cluster and Classification Techniques for the Biosciences
2006, Cambridge University Press
in English
0511259379 9780511259371
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6
Cluster and Classification Techniques for the Biosciences
2006, Cambridge University Press
eBook
in English
0511258070 9780511258077
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