Knowledge Discovery with Support Vector Machines / Wiley Series on Methods and Applications Bd.1 (PDF)
(Sprache: Englisch)
An easy-to-follow introduction to support vector machines
This book provides an in-depth, easy-to-follow introduction to
support vector machines drawing only from minimal, carefully
motivated technical and mathematical background material. It...
This book provides an in-depth, easy-to-follow introduction to
support vector machines drawing only from minimal, carefully
motivated technical and mathematical background material. It...
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An easy-to-follow introduction to support vector machines
This book provides an in-depth, easy-to-follow introduction to
support vector machines drawing only from minimal, carefully
motivated technical and mathematical background material. It begins
with a cohesive discussion of machine learning and goes on to
cover:
* Knowledge discovery environments
* Describing data mathematically
* Linear decision surfaces and functions
* Perceptron learning
* Maximum margin classifiers
* Support vector machines
* Elements of statistical learning theory
* Multi-class classification
* Regression with support vector machines
* Novelty detection
Complemented with hands-on exercises, algorithm descriptions,
and data sets, Knowledge Discovery with Support Vector
Machines is an invaluable textbook for advanced undergraduate
and graduate courses. It is also an excellent tutorial on support
vector machines for professionals who are pursuing research in
machine learning and related areas.
This book provides an in-depth, easy-to-follow introduction to
support vector machines drawing only from minimal, carefully
motivated technical and mathematical background material. It begins
with a cohesive discussion of machine learning and goes on to
cover:
* Knowledge discovery environments
* Describing data mathematically
* Linear decision surfaces and functions
* Perceptron learning
* Maximum margin classifiers
* Support vector machines
* Elements of statistical learning theory
* Multi-class classification
* Regression with support vector machines
* Novelty detection
Complemented with hands-on exercises, algorithm descriptions,
and data sets, Knowledge Discovery with Support Vector
Machines is an invaluable textbook for advanced undergraduate
and graduate courses. It is also an excellent tutorial on support
vector machines for professionals who are pursuing research in
machine learning and related areas.
Autoren-Porträt von Lutz H. Hamel
Lutz Hamel, PhD, teaches at the University of Rhode Island, where he founded the machine learning and data mining group. His major research interests are computational logic, machine learning, evolutionary computation, data mining, bioinformatics, and computational structures in art and literature.
Bibliographische Angaben
- Autor: Lutz H. Hamel
- 2009, 1. Auflage, 262 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 0470503041
- ISBN-13: 9780470503041
- Erscheinungsdatum: 04.11.2009
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Größe: 2.73 MB
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Sprache:
Englisch
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