Combining Pattern Classifiers – Methods and Algorithms, 2e
Seiten
2014
John Wiley & Sons Inc (Hersteller)
978-1-118-91456-4 (ISBN)
John Wiley & Sons Inc (Hersteller)
978-1-118-91456-4 (ISBN)
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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.
Thoroughly updated, with MATLAB(R) code and practice data sets throughout, Combining Pattern Classifiers includes:
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
With firm grounding in the fundamentals of pattern recognition, and featuring more than 140 illustrations, Combining Pattern Classifiers, Second Edition is a valuable reference for postgraduate students, researchers, and practitioners in computing and engineering.
Thoroughly updated, with MATLAB(R) code and practice data sets throughout, Combining Pattern Classifiers includes:
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
With firm grounding in the fundamentals of pattern recognition, and featuring more than 140 illustrations, Combining Pattern Classifiers, Second Edition is a valuable reference for postgraduate students, researchers, and practitioners in computing and engineering.
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.
| Erscheint lt. Verlag | 29.8.2014 |
|---|---|
| Verlagsort | New York |
| Sprache | englisch |
| Maße | 150 x 250 mm |
| Gewicht | 666 g |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| ISBN-10 | 1-118-91456-2 / 1118914562 |
| ISBN-13 | 978-1-118-91456-4 / 9781118914564 |
| Zustand | Neuware |
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