Error estimation for pattern recognition / (Record no. 42585)
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| fixed length control field | 08315nam a2200505 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 7198539 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | IEEE |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20191218152126.0 |
| 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 |n||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 151229s2015 maua ob 001 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781119079507 |
| Qualifying information | electronic |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Canceled/invalid ISBN | 9781118999738 |
| Qualifying information | hardback |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1002/9781119079507 |
| Source of number or code | doi |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (CaBNVSL)mat07198539 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (IDAMS)0b0000648497a1bd |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | CaBNVSL |
| Language of cataloging | eng |
| Description conventions | rda |
| Transcribing agency | CaBNVSL |
| Modifying agency | CaBNVSL |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q327 |
| Item number | .B73 2015eb |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 511.4/3 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Braga-Neto, Ulisses de Mendon A�Aca, |
| Relator term | author. |
| 245 10 - TITLE STATEMENT | |
| Title | Error estimation for pattern recognition / |
| Statement of responsibility, etc. | Ulisses M. Braga Neto, Edward R. Dougherty. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Chichester, West Sussex : |
| Name of producer, publisher, distributor, manufacturer | Wiley Blackwell, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2015. |
| 264 #2 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | [Piscataqay, New Jersey] : |
| Name of producer, publisher, distributor, manufacturer | IEEE Xplore, |
| Date of production, publication, distribution, manufacture, or copyright notice | [2015] |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 1 PDF (xxii, 336 pages) : |
| Other physical details | illustrations. |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | electronic |
| Source | isbdmedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Source | rdacarrier |
| 490 1# - SERIES STATEMENT | |
| Series statement | IEEE press series on biomedical engineering |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Includes bibliographical references (pages 291-300) and indexes. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | PREFACE XIII -- ACKNOWLEDGMENTS XIX -- LIST OF SYMBOLS XXI -- 1 CLASSIFICATION 1 -- 1.1 Classifiers 1 -- 1.2 Population-Based Discriminants 3 -- 1.3 Classification Rules 8 -- 1.4 Sample-Based Discriminants 13 -- 1.4.1 Quadratic Discriminants 14 -- 1.4.2 Linear Discriminants 15 -- 1.4.3 Kernel Discriminants 16 -- 1.5 Histogram Rule 16 -- 1.6 Other Classification Rules 20 -- 1.6.1 k-Nearest-Neighbor Rules 20 -- 1.6.2 Support Vector Machines 21 -- 1.6.3 Neural Networks 22 -- 1.6.4 Classification Trees 23 -- 1.6.5 Rank-Based Rules 24 -- 1.7 Feature Selection 25 -- Exercises 28 -- 2 ERROR ESTIMATION35 -- 2.1 Error Estimation Rules 35 -- 2.2 Performance Metrics 38 -- 2.2.1 Deviation Distribution 39 -- 2.2.2 Consistency 41 -- 2.2.3 Conditional Expectation 41 -- 2.2.4 Linear Regression 42 -- 2.2.5 Confidence Intervals 42 -- 2.3 Test-Set Error Estimation 43 -- 2.4 Resubstitution 46 -- 2.5 Cross-Validation 48 -- 2.6 Bootstrap 55 -- 2.7 Convex Error Estimation 57 -- 2.8 Smoothed Error Estimation 61 -- 2.9 Bolstered Error Estimation 63 -- 2.9.1 Gaussian-Bolstered Error Estimation 67 -- 2.9.2 Choosing the Amount of Bolstering 68 -- 2.9.3 Calibrating the Amount of Bolstering 71 -- Exercises 73 -- 3 PERFORMANCE ANALYSIS77 -- 3.1 Empirical Deviation Distribution 77 -- 3.2 Regression 79 -- 3.3 Impact on Feature Selection 82 -- 3.4 Multiple-Data-Set Reporting Bias 84 -- 3.5 Multiple-Rule Bias 86 -- 3.6 Performance Reproducibility 92 -- Exercises 94 -- 4 ERROR ESTIMATION FOR DISCRETE CLASSIFICATION 97 -- 4.1 Error Estimators 98 -- 4.1.1 Resubstitution Error 98 -- 4.1.2 Leave-One-Out Error 98 -- 4.1.3 Cross-Validation Error 99 -- 4.1.4 Bootstrap Error 99 -- 4.2 Small-Sample Performance 101 -- 4.2.1 Bias 101 -- 4.2.2 Variance 103 -- 4.2.3 Deviation Variance, RMS, and Correlation 105 -- 4.2.4 Numerical Example 106 -- 4.2.5 Complete Enumeration Approach 108 -- 4.3 Large-Sample Performance 110 -- Exercises 114 -- 5 DISTRIBUTION THEORY 115 -- 5.1 Mixture Sampling Versus Separate Sampling 115 -- 5.2 Sample-Based Discriminants Revisited 119 -- 5.3 True Error 120 -- 5.4 Error Estimators 121 -- 5.4.1 Resubstitution Error 121 -- 5.4.2 Leave-One-Out Error 122 -- 5.4.3 Cross-Validation Error 122 -- 5.4.4 Bootstrap Error 124 -- 5.5 Expected Error Rates 125 -- 5.5.1 True Error 125 -- 5.5.2 Resubstitution Error 128 -- 5.5.3 Leave-One-Out Error 130 -- 5.5.4 Cross-Validation Error 132 -- 5.5.5 Bootstrap Error 133 -- 5.6 Higher-Order Moments of Error Rates 136 -- 5.6.1 True Error 136 -- 5.6.2 Resubstitution Error 137 -- 5.6.3 Leave-One-Out Error 139 -- 5.7 Sampling Distribution of Error Rates 140 -- 5.7.1 Resubstitution Error 140 -- 5.7.2 Leave-One-Out Error 141 -- Exercises 142 -- 6 GAUSSIAN DISTRIBUTION THEORY: UNIVARIATE CASE 145 -- 6.1 Historical Remarks 146 -- 6.2 Univariate Discriminant 147 -- 6.3 Expected Error Rates 148 -- 6.3.1 True Error 148 -- 6.3.2 Resubstitution Error 151 -- 6.3.3 Leave-One-Out Error 152 -- 6.3.4 Bootstrap Error 152 -- 6.4 Higher-Order Moments of Error Rates 154 -- 6.4.1 True Error 154 -- 6.4.2 Resubstitution Error 157 -- 6.4.3 Leave-One-Out Error 160 -- 6.4.4 Numerical Example 165 -- 6.5 Sampling Distributions of Error Rates 166 -- 6.5.1 Marginal Distribution of Resubstitution Error 166 -- 6.5.2 Marginal Distribution of Leave-One-Out Error 169 -- 6.5.3 Joint Distribution of Estimated and True Errors 174 -- Exercises 176 -- 7 GAUSSIAN DISTRIBUTION THEORY: MULTIVARIATE CASE 179 -- 7.1 Multivariate Discriminants 179 -- 7.2 Small-Sample Methods 180 -- 7.2.1 Statistical Representations 181 -- 7.2.2 Computational Methods 194 -- 7.3 Large-Sample Methods 199 -- 7.3.1 Expected Error Rates 200 -- 7.3.2 Second-Order Moments of Error Rates 207 -- Exercises 218 -- 8 BAYESIAN MMSE ERROR ESTIMATION221 -- 8.1 The Bayesian MMSE Error Estimator 222 -- 8.2 Sample-Conditioned MSE 226 -- 8.3 Discrete Classification 227 -- 8.4 Linear Classification of Gaussian Distributions 238 -- 8.5 Consistency 246 -- 8.6 Calibration 253 -- 8.7 Concluding Remarks 255 -- Exercises 257 -- A BASIC PROBABILITY REVIEW 259 -- A.1 Sample Spaces and Events 259 -- A.2 Definition of Probability 260 -- A.3 Borel-Cantelli Lemmas 261 -- A.4 Conditional Probability 262 -- A.5 Random Variables 263 -- A.6 Discrete Random Variables 265 -- A.7 Expectation 266 -- A.8 Conditional Expectation 268 -- A.9 Variance 269 -- A.10 Vector Random Variables 270 -- A.11 The Multivariate Gaussian 271 -- A.12 Convergence of Random Sequences 273 -- A.13 Limiting Theorems 275 -- B VAPNIK-CHERVONENKIS THEORY 277 -- B.1 Shatter Coefficients 277 -- B.2 The VC Dimension 278 -- B.3 VC Theory of Classification 279 -- B.3.1 Linear Classification Rules 279 -- B.3.2 kNN Classification Rule 280 -- B.3.3 Classification Trees 280 -- B.3.4 Nonlinear SVMs 281 -- B.3.5 Neural Networks 281 -- B.3.6 Histogram Rules 281 -- B.4 Vapnik-Chervonenkis Theorem 282 -- C DOUBLE ASYMPTOTICS 285 -- BIBLIOGRAPHY 291 -- AUTHOR INDEX 301 -- SUBJECT INDEX 305. |
| 506 1# - RESTRICTIONS ON ACCESS NOTE | |
| Terms governing access | Restricted to subscribers or individual electronic text purchasers. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This book is the first of its kind to discuss error estimation with a model-based approach. From the basics of classifiers and error estimators to more specialized classifiers, it covers important topics and essential issues pertaining to the scientific validity of pattern classification. Error Estimation for Pattern Recognition focuses on error estimation, which is a broad and poorly understood topic that reaches all research areas using pattern classification. It includes model-based approaches and discussions of newer error estimators such as bolstered and Bayesian estimators. This book was motivated by the application of pattern recognition to high-throughput data with limited replicates, which is a basic problem now appearing in many areas. The first two chapters cover basic issues in classification error estimation, such as definitions, test-set error estimation, and training-set error estimation. The remaining chapters in this book cover results on the performance and representation of training-set error estimators for various pattern classifiers. Additional features of the book include: . The latest results on the accuracy of error estimation. Performance analysis of resubstitution, cross-validation, and bootstrap error estimators using analytical and simulation approaches. Highly interactive computer-based exercises and end-of-chapter Problems This is the first book exclusively about error estimation for pattern recognition. |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE | |
| Additional physical form available note | Also available in print. |
| 538 ## - SYSTEM DETAILS NOTE | |
| System details note | Mode of access: World Wide Web |
| 588 ## - SOURCE OF DESCRIPTION NOTE | |
| Source of description note | Description based on PDF viewed 12/29/2015. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Pattern perception |
| General subdivision | Mathematics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Error analysis (Mathematics) |
| 655 #0 - INDEX TERM--GENRE/FORM | |
| Genre/form data or focus term | Electronic books. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dougherty, Edward R., |
| Relator term | author. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | IEEE Xplore (Online Service), |
| Relator term | distributor. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Wiley, |
| Relator term | publisher. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Print version: |
| International Standard Book Number | 9781118999738 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | IEEE press series on biomedical engineering |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Abstract with links to resource |
| Uniform Resource Identifier | https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=7198539 |
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