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Cluster and classification techniques for the biosciences /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Cluster and classification techniques for the biosciences // Alan H. Fielding.
remainder title:	Cluster & Classification Techniques for the Biosciences
Author:	Fielding, Alan,
Description:	1 online resource (xii, 246 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Subject:	Biology - Data processing. -
Online resource:	https://doi.org/10.1017/CBO9780511607493
ISBN:	9780511607493 (ebook)

Cluster and classification techniques for the biosciences /
Fielding, Alan,

Cluster and classification techniques for the biosciences /Cluster & Classification Techniques for the BiosciencesAlan H. Fielding. - 1 online resource (xii, 246 pages) :digital, PDF file(s).

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Exploratory data analysis -- Cluster analysis -- Introduction to classification -- Classification algorithms -- Other classification methods -- Classification accuracy.

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 2006 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.

ISBN: 9780511607493 (ebook)Subjects--Topical Terms:

563885
Biology
--Data processing.

LC Class. No.: QH324.2 / .F537 2007

Dewey Class. No.: 570.285

Cluster and classification techniques for the biosciences /
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520 $a 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 2006 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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