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    Knowledge Discovery with Support Vector Machines

    Posted By: step778
    Knowledge Discovery with Support Vector Machines

    Lutz H. Hamel, "Knowledge Discovery with Support Vector Machines"
    2009 | pages: 267 | ISBN: 0470371927 | PDF | 2 mb

    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.

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