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Data Complexity in Pattern Recognition - Mitra Basu (Editor), Tin Kam Ho (Editor)
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ISBN: 9781849965576

ID: 9781849965576

Machines capable of automatic pattern recognition have many fascinating uses in science and engineering as well as in our daily lives. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. Tremendous progress has been made in refining such algorithms; yet, automatic learning in many simple tasks in daily life still appears to be far from reach. This book takes a close view of data complexity and Machines capable of automatic pattern recognition have many fascinating uses in science and engineering as well as in our daily lives. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. Tremendous progress has been made in refining such algorithms; yet, automatic learning in many simple tasks in daily life still appears to be far from reach. This book takes a close view of data complexity and its role in shaping the theories and techniques in different disciplines and asks: What is missing from current classification techniques? When the automatic classifiers are not perfect, is it a deficiency of the algorithms by design, or is it a difficulty intrinsic to the classification task? How do we know whether we have exploited to the fullest extent the knowledge embedded in the training data? Data Complexity in Pattern Recognition is unique in its comprehensive coverage and multidisciplinary approach from various methodological and practical perspectives. Researchers and practitioners alike will find this book an insightful reference to learn about the current status of available techniques as well as application areas. Textbooks New, Books~~Computers~~Intelligence (AI) & Semantics, Data-Complexity-in-Pattern-Recognition~~Mitra-Basu, 999999999, Data Complexity in Pattern Recognition, Mitra Basu (Editor), Tin Kam Ho (Editor), 1849965579, Springer London, , , , , Springer London

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ISBN: 9781849965576

Machines capable of automatic pattern recognition have many fascinating uses in science and engineering as well as in our daily lives. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. Tremendous progress has been made in refining such algorithms; yet, automatic learning in many simple tasks in daily life still appears to be far from reach.This book takes a close view of data complexity and its role in shaping the theories and techniques in different disciplines and asks:• What is missing from current classification techniques?• When the automatic classifiers are not perfect, is it a deficiency of the algorithms by design, or is it a difficulty intrinsic to the classification task? • How do we know whether we have exploited to the fullest extent the knowledge embedded in the training data? Data Complexity in Pattern Recognition is unique in its comprehensive coverage and multidisciplinary approach from various methodological and practical perspectives. Researchers and practitioners alike will find this book an insightful reference to learn about the current status of available techniques as well as application areas. Textbooks New Books ~~ Computers~~ Intelligence (AI) & Semantics Data-Complexity-in-Pattern-Recognition~~Mitra-Basu Springer London Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.

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Data Complexity in Pattern Recognition - Taschenbuch

2010

ISBN: 1849965579

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Internationaler Buchtitel. In englischer Sprache. Verlag: Springer-Verlag GmbH, Paperback, 316 Seiten, L=235mm, B=155mm, H=17mm, Gew.=480gr, [GR: 16350 - HC/Anwendungs-Software], Kartoniert/Broschiert, Klappentext: Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance. Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.

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Data Complexity in Pattern Recognition
Autor:

Mitra Basu (Editor), Tin Kam Ho (Editor)

Titel:

Data Complexity in Pattern Recognition

ISBN-Nummer:

1849965579

Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.

Detailangaben zum Buch - Data Complexity in Pattern Recognition


EAN (ISBN-13): 9781849965576
ISBN (ISBN-10): 1849965579
Taschenbuch
Erscheinungsjahr: 2010
Herausgeber: Springer-Verlag GmbH
316 Seiten
Gewicht: 0,480 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 17.12.2011 02:50:20
Buch zuletzt gefunden am 23.02.2015 17:19:43
ISBN/EAN: 1849965579

ISBN - alternative Schreibweisen:
1-84996-557-9, 978-1-84996-557-6

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