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Statistical pattern recognition. (Record no. 11374)

MARC details
000 -LEADER
fixed length control field 08342cam a2200697Ka 4500
001 - CONTROL NUMBER
control field ocn760091928
003 - CONTROL NUMBER IDENTIFIER
control field OCoLC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20171224113737.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cnu---unuuu
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 111109s2011 enka ob 001 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency N$T
Language of cataloging eng
Description conventions pn
Transcribing agency N$T
Modifying agency YDXCP
-- DG1
-- TEFOD
-- UPM
-- OCLCQ
-- OCLCF
-- RRP
-- TEFOD
-- OCLCQ
-- DG1
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781119952954
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1119952956
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781119952961
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1119952964
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 9780470682272
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 0470682272
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 9780470682289
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 0470682280
029 1# - (OCLC)
OCLC library identifier NZ1
System control number 14695716
029 1# - (OCLC)
OCLC library identifier NZ1
System control number 15290911
029 1# - (OCLC)
OCLC library identifier NZ1
System control number 15412280
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)760091928
037 ## - SOURCE OF ACQUISITION
Stock number FF02F8CD-7AC4-4372-BFD9-3D8B02EE5199
Source of stock number/acquisition OverDrive, Inc.
Note http://www.overdrive.com
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q327
Item number W43 2011eb
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 047000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.4
Edition number 23
049 ## - LOCAL HOLDINGS (OCLC)
Holding library MAIN
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Webb, A. R.
Fuller form of name (Andrew R.)
245 10 - TITLE STATEMENT
Title Statistical pattern recognition.
250 ## - EDITION STATEMENT
Edition statement 3rd ed. /
Remainder of edition statement Andrew R. Webb, Keith D. Copsey, Gavin Cawley.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Oxford :
Name of publisher, distributor, etc Wiley-Blackwell,
Date of publication, distribution, etc 2011.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xxiv, 642 pages) :
Other physical details illustrations
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
500 ## - GENERAL NOTE
General note Previous edition: New York: Wiley, 2002.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
588 0# -
-- Print version record.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Note continued: 9.3.Comparing Classifier Performance -- 9.3.1. Which Technique is Best? -- 9.3.2. Statistical Tests -- 9.3.3.Comparing Rules When Misclassification Costs are Uncertain -- 9.3.4. Example Application Study -- 9.3.5. Further Developments -- 9.3.6. Summary -- 9.4. Application Studies -- 9.5. Summary and Discussion -- 9.6. Recommendations -- 9.7. Notes and References -- Exercises -- 10. Feature Selection and Extraction -- 10.1. Introduction -- 10.2. Feature Selection -- 10.2.1. Introduction -- 10.2.2. Characterisation of Feature Selection Approaches -- 10.2.3. Evaluation Measures -- 10.2.4. Search Algorithms for Feature Subset Selection -- 10.2.5.Complete Search -- Branch and Bound -- 10.2.6. Sequential Search -- 10.2.7. Random Search -- 10.2.8. Markov Blanket -- 10.2.9. Stability of Feature Selection -- 10.2.10. Example Application Study -- 10.2.11. Further Developments -- 10.2.12. Summary -- 10.3. Linear Feature Extraction -- 10.3.1. Principal Components Analysis -- 10.3.2. Karhunen-Loeve Transformation -- 10.3.3. Example Application Study -- 10.3.4. Further Developments -- 10.3.5. Summary -- 10.4. Multidimensional Scaling -- 10.4.1. Classical Scaling -- 10.4.2. Metric MDS -- 10.4.3. Ordinal Scaling -- 10.4.4. Algorithms -- 10.4.5. MDS for Feature Extraction -- 10.4.6. Example Application Study -- 10.4.7. Further Developments -- 10.4.8. Summary -- 10.5. Application Studies -- 10.6. Summary and Discussion -- 10.7. Recommendations -- 10.8. Notes and References -- Exercises -- 11. Clustering -- 11.1. Introduction -- 11.2. Hierarchical Methods -- 11.2.1. Single-Link Method -- 11.2.2.Complete-Link Method -- 11.2.3. Sum-of-Squares Method -- 11.2.4. General Agglomerative Algorithm -- 11.2.5. Properties of a Hierarchical Classification -- 11.2.6. Example Application Study -- 11.2.7. Summary -- 11.3. Quick Partitions -- 11.4. Mixture Models -- 11.4.1. Model Description -- 11.4.2. Example Application Study -- 11.5. Sum-of-Squares Methods -- 11.5.1. Clustering Criteria -- 11.5.2. Clustering Algorithms -- 11.5.3. Vector Quantisation -- 11.5.4. Example Application Study -- 11.5.5. Further Developments -- 11.5.6. Summary -- 11.6. Spectral Clustering -- 11.6.1. Elementary Graph Theory -- 11.6.2. Similarity Matrices -- 11.6.3. Application to Clustering -- 11.6.4. Spectral Clustering Algorithm -- 11.6.5. Forms of Graph Laplacian -- 11.6.6. Example Application Study -- 11.6.7. Further Developments -- 11.6.8. Summary -- 11.7. Cluster Validity -- 11.7.1. Introduction -- 11.7.2. Statistical Tests -- 11.7.3. Absence of Class Structure -- 11.7.4. Validity of Individual Clusters -- 11.7.5. Hierarchical Clustering -- 11.7.6. Validation of Individual Clusterings -- 11.7.7. Partitions -- 11.7.8. Relative Criteria -- 11.7.9. Choosing the Number of Clusters -- 11.8. Application Studies -- 11.9. Summary and Discussion -- 11.10. Recommendations -- 11.11. Notes and References -- Exercises -- 12.Complex Networks -- 12.1. Introduction -- 12.1.1. Characteristics -- 12.1.2. Properties -- 12.1.3. Questions to Address -- 12.1.4. Descriptive Features -- 12.1.5. Outline -- 12.2. Mathematics of Networks -- 12.2.1. Graph Matrices -- 12.2.2. Connectivity -- 12.2.3. Distance Measures -- 12.2.4. Weighted Networks -- 12.2.5. Centrality Measures -- 12.2.6. Random Graphs -- 12.3.Community Detection -- 12.3.1. Clustering Methods -- 12.3.2. Girvan-Newman Algorithm -- 12.3.3. Modularity Approaches -- 12.3.4. Local Modularity -- 12.3.5. Clique Percolation -- 12.3.6. Example Application Study -- 12.3.7. Further Developments -- 12.3.8. Summary -- 12.4. Link Prediction -- 12.4.1. Approaches to Link Prediction -- 12.4.2. Example Application Study -- 12.4.3. Further Developments -- 12.5. Application Studies -- 12.6. Summary and Discussion -- 12.7. Recommendations -- 12.8. Notes and References -- Exercises -- 13. Additional Topics -- 13.1. Model Selection -- 13.1.1. Separate Training and Test Sets -- 13.1.2. Cross-Validation -- 13.1.3. The Bayesian Viewpoint -- 13.1.4. Akaike's Information Criterion -- 13.1.5. Minimum Description Length -- 13.2. Missing Data -- 13.3. Outlier Detection and Robust Procedures -- 13.4. Mixed Continuous and Discrete Variables -- 13.5. Structural Risk Minimisation and the Vapnik-Chervonenkis Dimension -- 13.5.1. Bounds on the Expected Risk -- 13.5.2. The VC Dimension.
520 ## - SUMMARY, ETC.
Summary, etc "Statistical Pattern Recognition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. The book describes techniques for analysing data comprising measurements made on individuals or objects. The techniques are used to make a prediction such as disease of a patient, the type of object illuminated by a radar, economic forecast. Emphasis is placed on techniques for classification, a term used for predicting the class or group an object belongs to (based on a set of exemplars) and for methods that seek to discover natural groupings in a data set. Each section concludes with a description of the wide range of practical applications that have been addressed and the further developments of theoretical techniques and includes a variety of exercises, from 'open-book' questions to more lengthy projects. New material is presented, including the analysis of complex networks and basic techniques for analysing the properties of datasets and also introduces readers to the use of variational methods for Bayesian density estimation and looks at new applications in biometrics and security."--
-- Provided by publisher.
520 ## - SUMMARY, ETC.
Summary, etc "The book describes techniques for analysing data comprising measurements made on individuals or objects."--
-- Provided by publisher.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Pattern perception
General subdivision Statistical methods.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Decision making
General subdivision Mathematical models.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical statistics.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element COMPUTERS
General subdivision Optical Data Processing.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Decision making
General subdivision Mathematical models.
Source of heading or term fast
-- (OCoLC)fst00889048
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical statistics.
Source of heading or term fast
-- (OCoLC)fst01012127
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Pattern perception
General subdivision Statistical methods.
Source of heading or term fast
-- (OCoLC)fst01055263
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Copsey, Keith D.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Cawley, Gavin.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Print version:
Main entry heading Webb, A.R. (Andrew R.).
Title Statistical pattern recognition.
Edition 3rd ed.
Place, publisher, and date of publication Oxford : Wiley-Blackwell, 2011
International Standard Book Number 9780470682272
Record control number (OCoLC)751717289
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://onlinelibrary.wiley.com/book/10.1002/9781119952954">http://onlinelibrary.wiley.com/book/10.1002/9781119952954</a>
Public note Wiley Online Library
938 ## -
-- EBSCOhost
-- EBSC
-- 398587
938 ## -
-- YBP Library Services
-- YANK
-- 7188105
938 ## -
-- YBP Library Services
-- YANK
-- 7461474
938 ## -
-- YBP Library Services
-- YANK
-- 7598341
994 ## -
-- 92
-- DG1

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