Overview
Biometric System and Data Analysis: Design, Evaluation, and Data Mining brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluate, interpret and understand biometric data. This professional book naturally leads to topics including data mining and prediction--widely applied to other fields but not rigorously to biometrics--to be examined in detail. This volume places an emphasis on the various performance measures available for biometric systems, what they mean, and when they should and should not be applied. The evaluation techniques are presented rigorously, however are always accompanied by intuitive explanations that convey the essence of the statistical concepts to a general audience. Designed for a professional audience composed of practitioners and researchers in industry, Biometric System and Data Analysis: Design, Evaluation, and Data Mining is also suitable as a reference for advanced-level students in computer science and engineering.
Full Product Details
Author: Ted Dunstone ,
Neil Yager
Publisher: Springer-Verlag New York Inc.
Imprint: Springer-Verlag New York Inc.
Edition: 2009 ed.
Dimensions:
Width: 15.50cm
, Height: 1.70cm
, Length: 23.50cm
Weight: 1.280kg
ISBN: 9780387776255
ISBN 10: 0387776257
Pages: 268
Publication Date: 02 December 2008
Audience:
College/higher education
,
Professional and scholarly
,
Undergraduate
,
Postgraduate, Research & Scholarly
Format: Hardback
Publisher's Status: Active
Availability: In Print
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Reviews
From the reviews: This book brings together a discussion on biometric systems, statistics, and machine learning. Its aim is to help us understand biometric data, measurements of such systems, and the ability to interpret them is highly desirable. ... The book suits the needs of many practitioners, those involved with data in all its forms, and also would make useful reading for those who are studying systems, cybernetics, and management in the many and varied courses now being made available worldwide. (W. R. Howard, Kybernetes, Vol. 38 (9), 2009)
From the reviews: This book brings together a discussion on biometric systems, statistics, and machine learning. Its aim is to help us understand biometric data, measurements of such systems, and the ability to interpret them is highly desirable. The book suits the needs of many practitioners, those involved with data in all its forms, and also would make useful reading for those who are studying systems, cybernetics, and management in the many and varied courses now being made available worldwide. (W. R. Howard, Kybernetes, Vol. 38 (9), 2009)
