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Learning with Kernels
Support Vector Machines, Regularization, Optimization, and Beyond
Taschenbuch von Alexander J. Smola
Sprache: Englisch

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Beschreibung
A comprehensive introduction to Support Vector Machines and related kernel methods.

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics.

Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

A comprehensive introduction to Support Vector Machines and related kernel methods.

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics.

Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

Über den Autor
Bernhard Schölkopf is Director at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He is coauthor of Learning with Kernels (2002) and is a coeditor of Advances in Kernel Methods: Support Vector Learning (1998), Advances in Large-Margin Classifiers (2000), and Kernel Methods in Computational Biology (2004), all published by the MIT Press. Alexander J. Smola is Senior Principal Researcher and Machine Learning Program Leader at National ICT Australia/Australian National University, Canberra.
Details
Erscheinungsjahr: 2018
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 646
ISBN-13: 9780262536578
ISBN-10: 0262536579
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Smola, Alexander J.
Hersteller: MIT Press
Maße: 254 x 203 x 35 mm
Von/Mit: Alexander J. Smola
Erscheinungsdatum: 05.06.2018
Gewicht: 1,363 kg
preigu-id: 113981731
Über den Autor
Bernhard Schölkopf is Director at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He is coauthor of Learning with Kernels (2002) and is a coeditor of Advances in Kernel Methods: Support Vector Learning (1998), Advances in Large-Margin Classifiers (2000), and Kernel Methods in Computational Biology (2004), all published by the MIT Press. Alexander J. Smola is Senior Principal Researcher and Machine Learning Program Leader at National ICT Australia/Australian National University, Canberra.
Details
Erscheinungsjahr: 2018
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 646
ISBN-13: 9780262536578
ISBN-10: 0262536579
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Smola, Alexander J.
Hersteller: MIT Press
Maße: 254 x 203 x 35 mm
Von/Mit: Alexander J. Smola
Erscheinungsdatum: 05.06.2018
Gewicht: 1,363 kg
preigu-id: 113981731
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