Author: Alan H. Fielding
Edition: 1
Publisher: Cambridge University Press
Binding: Paperback
ISBN: 0521618002
Cluster and Classification Techniques for the Biosciences
Recent advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Medical books Cluster and Classification Techniques for the Biosciences. 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 Medical books Cluster and Classification Techniques for the Biosciences. Cluster and Classification Techniques for the Biosciences
Download link for Cluster and classification techniques for the biosciences
Cluster and Classification Techniques for the Biosciences
Cluster and Classification Techniques for the Biosciences Cambridge University Press 9780521852814 09780521852814
Cambridge University Press. Hardcover. 0521852811 Hardcover; 2007 Cambridge University Press; 258 pages; "Cluster and Classification Techniques for the Biosciences" by Alan H. Fielding. . Good.
author alan fielding format hardback language english publication year 14 12 2006 subject mathematics sciences subject 2 life sciences general cluster and classification techniques for the biosciences by alan h fielding published by cambridge university press not quite what you re looking for see more books in ecology or biological life sciences all free uk delivery on everything not even the right subject see books in arts design and entertainment business and commerce computing and it history
Medical Book Cluster and Classification Techniques for the Biosciences
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.
