Statistical pattern recognition. (Record no. 62855)
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| fixed length control field | 08390cam a2200697Ka 4500 |
| 001 - CONTROL NUMBER | |
| control field | sulb-eb0031203 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | BD-SySUS |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20170713221251.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS | |
| 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 |
| -- | BD-SySUS |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781119952954 |
| Qualifying information | (electronic bk.) |
| International Standard Book Number | 1119952956 |
| Qualifying information | (electronic bk.) |
| International Standard Book Number | 9781119952961 |
| Qualifying information | (electronic bk.) |
| International Standard Book Number | 1119952964 |
| Qualifying information | (electronic bk.) |
| Canceled/invalid ISBN | 9780470682272 |
| Canceled/invalid ISBN | 0470682272 |
| Canceled/invalid ISBN | 9780470682289 |
| Canceled/invalid ISBN | 0470682280 |
| 029 1# - OTHER SYSTEM CONTROL NUMBER (OCLC) | |
| OCLC library identifier | NZ1 |
| System control number | 14695716 |
| OCLC library identifier | NZ1 |
| System control number | 15290911 |
| 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 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | 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# - SOURCE OF DESCRIPTION NOTE | |
| Source of description note | 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."-- |
| Assigning source | Provided by publisher. |
| Summary, etc. | "The book describes techniques for analysing data comprising measurements made on individuals or objects."-- |
| Assigning source | Provided by publisher. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Pattern perception |
| General subdivision | Statistical methods. |
| Topical term or geographic name as entry element | Decision making |
| General subdivision | Mathematical models. |
| Topical term or geographic name as entry element | Mathematical statistics. |
| Topical term or geographic name as entry element | COMPUTERS |
| General subdivision | Optical Data Processing. |
| Source of heading or term | bisacsh |
| Topical term or geographic name as entry element | Decision making |
| General subdivision | Mathematical models. |
| Source of heading or term | fast |
| Authority record control number | (OCoLC)fst00889048 |
| Topical term or geographic name as entry element | Mathematical statistics. |
| Source of heading or term | fast |
| Authority record control number | (OCoLC)fst01012127 |
| Topical term or geographic name as entry element | Pattern perception |
| General subdivision | Statistical methods. |
| Source of heading or term | fast |
| Authority record control number | (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. |
| Personal name | Cawley, Gavin. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | 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 [Free Download only for SUST IP] |
| 938 ## - | |
| -- | EBSCOhost |
| -- | EBSC |
| -- | 398587 |
| -- | YBP Library Services |
| -- | YANK |
| -- | 7188105 |
| -- | YBP Library Services |
| -- | YANK |
| -- | 7461474 |
| -- | YBP Library Services |
| -- | YANK |
| -- | 7598341 |
| 994 ## - | |
| -- | 92 |
| -- | DG1 |
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