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Knowledge Discovery with Support Vector Machines
     

Knowledge Discovery with Support Vector Machines

by Lutz H. Hamel
 

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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

Overview

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.

Product Details

ISBN-13:
9781118211038
Publisher:
Wiley
Publication date:
09/20/2011
Series:
Wiley Series on Methods and Applications in Data Mining , #3
Sold by:
Barnes & Noble
Format:
NOOK Book
Pages:
246
File size:
9 MB

Meet the Author

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.

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