Enhancing Kernel Methods Pattern by Tang (12 results)

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Taschenbuch. Condition: Neu. Enhancing Kernel Methods for Pattern Classification | Theories and Implementations | Ke Tang | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2009 | VDM Verlag Dr. Müller | EAN 9783639182606 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. …

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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Tang KeKe Tang, Ph.D: Obtained his Ph.D degree from Nanyang nTechnological University, Singapore. He is currently an nassociate professor with the School of Computer Science and nTechnology, University of Science and Technology of Ch.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Kernel methods are a new family of techniques with sound theoretical grounds. They have been shown to be powerful approaches to pattern classification problems. However, many of the newly created kernel methods are far from perfect, andextensions and improvements are always required to make them even more effective. This book investigates one important class of the kernel methods, the least square support vector machines (LS-SVM), and enhances its performance extensively. In particular, the LS-SVM is enhanced in the contexts of four sub-problems related to solving the pattern classification problem. That is, model selection, feature selection, building sparse kernel classifier and kernel classifier ensemble. The LS-SVM can be regarded as a representative of many other kernel methods, and thus many ideas presented in this book can be easily extended to enhance performance of those related kernel methods. The results obtained should be useful to professionals that work on the theoretical aspects of kernel methods, or anyone else who may be considering ustilizing kernel methods for real-world pattern classification problems.…

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