Support vector machines optimization based theory, algorithms, and extensions

"Preface Support vector machines (SVMs), which were introduced by Vapnik in the early 1990s, are proved effective and promising techniques for data mining. SVMs have recently been breakthroughs in advance in their theoretical studies and implementations of algorithms. They have been successfull...

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Detalles Bibliográficos
Autor principal: Deng, Naiyang (-)
Otros Autores: Tian, Yingjie, 1973-, Zhang, Chunhua, 1978-
Formato: Libro electrónico
Idioma:Inglés
Publicado: Boca Raton : CRC Press, Taylor & Francis Group 2013.
Edición:1st edition
Colección:Chapman & Hall/CRC data mining and knowledge discovery series.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628516306719
Descripción
Sumario:"Preface Support vector machines (SVMs), which were introduced by Vapnik in the early 1990s, are proved effective and promising techniques for data mining. SVMs have recently been breakthroughs in advance in their theoretical studies and implementations of algorithms. They have been successfully applied in many fields such as text categorization, speech recognition, remote sensing image analysis, time series forecasting, information security and etc. SVMs, having their roots in Statistical Learning Theory (SLT) and optimization methods, become powerful tools to solve the problems of machine learning with finite training points and to overcome some traditional difficulties such as the "curse of dimensionality", "over-fitting" and etc. SVMs theoretical foundation and implementation techniques have been established and SVMs are gaining quick development and popularity due to their many attractive features: nice mathematical representations, geometrical explanations, good generalization abilities and promising empirical performance. Some SVM monographs, including more sophisticated ones such as Cristianini & Shawe-Taylor [39] and Scholkopf & Smola [124], have been published. We have published two books about SVMs in Science Press of China since 2004 [42, 43], which attracted widespread concerns and received favorable comments. After several years research and teaching, we decide to rewrite the books and add new research achievements. The starting point and focus of the book is optimization theory, which is different from other books on SVMs in this respect. Optimization is one of the pillars on which SVMs are built, so it makes a lot of sense to consider them from this point of view"--
Notas:"A Chapman & Hall book."
Descripción Física:1 online resource (345 p.)
Bibliografía:Includes bibliographical references (p. 299-313).
ISBN:9780429110283
9781439857939