Combining Pattern Classifiers: Methods and Algorithms 2nd Edition, 2/e
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Combining Pattern Classifiers: Methods and Algorithms 2nd Edition, 2/e

Author : Ludmila Kuncheva
© Year : 2014
ISBN : 9781118315231
Pages : 384
Binding : Hardback
Weight : 0.80   kg

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  • About the Book
  • Salient Features
  • Table of Contents
  • About the Author

A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition
The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004. Dr. Kuncheva has plucked from the rich landscape of recent classifier ensemble literature the topics, methods, and algorithms that will guide the reader toward a deeper understanding of the fundamentals, design, and applications of classifier ensemble methods.

Coverage of Bayes decision theory and experimental comparison of classifiers
Essential ensemble methods such as Bagging, Random forest, AdaBoost, Random subspace, Rotation forest, Random oracle, and Error Correcting Output Code, among others
Chapters on classifier selection, diversity, and ensemble feature selection

Preface xv
Acknowledgements xxi
1.Fundamentals of Pattern Recognition 1
2.Base Classifiers 49
3.An Overview of the Field 94
4.Combining Label Outputs 111
5.Combining Continuous-Valued Outputs 143
6.Ensemble Methods 186
7.Classifier Selection 230
8.Diversity in Classifier Ensembles 247
9.Ensemble Feature Selection 290
10. A Final Thought 326
References 327
Index 353

Ludmila Kuncheva :- Ludmila Kuncheva is a Professor of Computer Science at Bangor University, United Kingdom. She has received two IEEE Best Paper awards. In 2012, Dr. Kuncheva was awarded a Fellowship to the International Association for Pattern Recognition (IAPR) for her contributions to multiple classifier systems.

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