Knowledge Discovery with Support Vector Machines by Lutz H. Hamel
(Wiley Series on Methods and Applications in Data Mining)

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Synopsis

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.

 

About Lutz H. Hamel

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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.
 
Published September 21, 2011 by Wiley-Interscience. 246 pages
Genres: Computers & Technology. Non-fiction

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