Data Complexity in Pattern Recognition
Basu, Mitra; Ho, Tin Kam
ISBN 10: 1849965579 ISBN 13: 9781849965576
Published by Springer, 2010
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A unique book for researchers and practitioners across disciplines (including Computer Science, Engineering, Social Science and Finance) to learn about the current status, available techniques, and applications of data complexity in pattern recognition.
From the Back Cover:
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.
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Title: Data Complexity in Pattern Recognition
Publisher: Springer
Publication Date: 2010
Binding: Soft cover
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Data Complexity in Pattern Recognition (eng)
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Shows how to appreciate the presence and nature of patterns in specific problemsHelps the reader set proper expectations for classification performanceOffers guidance on choosing the best pattern recognition classification tec. Seller Inventory # 4288684
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Taschenbuch. Condition: Neu. Data Complexity in Pattern Recognition | Mitra Basu (u. a.) | Taschenbuch | xvi | Englisch | 2010 | Springer | EAN 9781849965576 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 107247801
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 316 pp. Englisch. Seller Inventory # 9781849965576
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A unique book for researchers and practitioners across disciplines (including Computer Science, Engineering, Social Science and Finance) to learn about the current status, available techniques, and applications of data complexity in pattern recognition.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 316 pp. Englisch. Seller Inventory # 9781849965576
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machines capable of automatic pattern recognition have many fascinating uses in science & 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.This book takes a close view of data complexity & its role in shaping the theories & techniques in different disciplines & 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 Uunique in its comprehensive coverage & multidisciplinary approach from various methodological & practical perspectives, researchers & practitioners will find this book an insightful reference to learn about current available techniques as well as application areas. Seller Inventory # 9781849965576
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