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Advances in Proximal Kernel Classifiers: Proximal Kernel Classifiers and its Application with MATLAB - Softcover
Inhaltsangabe
The book describes the development and performance of proximal classifiers, a class of kernel-based regularized mean square error type classifier that learns within the penalized modeling paradigm. The name proximal classifier indicates the fact of classification of a test pattern by its proximity either to a hyperplane or to a class centroid. The basic idea of the nonparallel plane classifier is to model each class of data by fitting separate hyperplane through it. A computationally efficient binary Nonparallel Plane Proximal Classifier (NPPC) is described in detail along with its nonlinear extension. NPPC is also extended to classify multiclass data. A new approach of multiclass data classification through vector-valued regression technique by the proximity to a class centroid is described in detail. These classifiers are applied to discriminate cancerous tissue samples from gene microarray data. The book provides a complete literature survey in the field of Support Vector Machine (SVM). It includes mathematical models, detailed solution procedures and algorithms of the different proximal classifiers with hands-on examples and well-documented MATLAB programs.
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Über die Autorin bzw. den Autor
Santanu Ghorai received the ME degree in electrical engineering from the Jadavpur University in 2000 and the PhD degree from the Indian Institute of Technology, Kharagpur, in 2011. Currently he is with the Heritage Institute of Technology, Kolkata. His principal research interests include signal processing, machine learning and bioinformatics.
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Advances in Proximal Kernel Classifiers
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 365927836X
ISBN 13: 9783659278365
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Softcover
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ghorai SantanuSantanu Ghorai received the ME degree in electrical engineering from the Jadavpur University in 2000 and the PhD degree from the Indian Institute of Technology, Kharagpur, in 2011. Currently he is with the Heritage Inst. Bestandsnummer des Verkäufers 5145199
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Advances in Proximal Kernel Classifiers
Verlag:
LAP LAMBERT Academic Publishing Nov 2012, 2012
ISBN 10: 365927836X
ISBN 13: 9783659278365
Neu
Taschenbuch
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Taschenbuch. Zustand: Neu. Neuware -The book describes the development and performance of proximal classifiers, a class of kernel-based regularized mean square error type classifier that learns within the penalized modeling paradigm. The name proximal classifier indicates the fact of classification of a test pattern by its proximity either to a hyperplane or to a class centroid. The basic idea of the nonparallel plane classifier is to model each class of data by fitting separate hyperplane through it. A computationally efficient binary Nonparallel Plane Proximal Classifier (NPPC) is described in detail along with its nonlinear extension. NPPC is also extended to classify multiclass data. A new approach of multiclass data classification through vector-valued regression technique by the proximity to a class centroid is described in detail. These classifiers are applied to discriminate cancerous tissue samples from gene microarray data. The book provides a complete literature survey in the field of Support Vector Machine (SVM). It includes mathematical models, detailed solution procedures and algorithms of the different proximal classifiers with hands-on examples and well-documented MATLAB programs.Books on Demand GmbH, Überseering 33, 22297 Hamburg 244 pp. Englisch. Bestandsnummer des Verkäufers 9783659278365
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Advances in Proximal Kernel Classifiers : Proximal Kernel Classifiers and its Application with MATLAB
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 365927836X
ISBN 13: 9783659278365
Neu
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Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book describes the development and performance of proximal classifiers, a class of kernel-based regularized mean square error type classifier that learns within the penalized modeling paradigm. The name proximal classifier indicates the fact of classification of a test pattern by its proximity either to a hyperplane or to a class centroid. The basic idea of the nonparallel plane classifier is to model each class of data by fitting separate hyperplane through it. A computationally efficient binary Nonparallel Plane Proximal Classifier (NPPC) is described in detail along with its nonlinear extension. NPPC is also extended to classify multiclass data. A new approach of multiclass data classification through vector-valued regression technique by the proximity to a class centroid is described in detail. These classifiers are applied to discriminate cancerous tissue samples from gene microarray data. The book provides a complete literature survey in the field of Support Vector Machine (SVM). It includes mathematical models, detailed solution procedures and algorithms of the different proximal classifiers with hands-on examples and well-documented MATLAB programs. Bestandsnummer des Verkäufers 9783659278365
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Advances in Proximal Kernel Classifiers
Verlag:
LAP LAMBERT Academic Publishing Nov 2012, 2012
ISBN 10: 365927836X
ISBN 13: 9783659278365
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book describes the development and performance of proximal classifiers, a class of kernel-based regularized mean square error type classifier that learns within the penalized modeling paradigm. The name proximal classifier indicates the fact of classification of a test pattern by its proximity either to a hyperplane or to a class centroid. The basic idea of the nonparallel plane classifier is to model each class of data by fitting separate hyperplane through it. A computationally efficient binary Nonparallel Plane Proximal Classifier (NPPC) is described in detail along with its nonlinear extension. NPPC is also extended to classify multiclass data. A new approach of multiclass data classification through vector-valued regression technique by the proximity to a class centroid is described in detail. These classifiers are applied to discriminate cancerous tissue samples from gene microarray data. The book provides a complete literature survey in the field of Support Vector Machine (SVM). It includes mathematical models, detailed solution procedures and algorithms of the different proximal classifiers with hands-on examples and well-documented MATLAB programs. 244 pp. Englisch. Bestandsnummer des Verkäufers 9783659278365
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Advances in Proximal Kernel Classifiers
Verlag:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2012
ISBN 10: 365927836X
ISBN 13: 9783659278365
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Zustand: New. pp. 244. Bestandsnummer des Verkäufers 26128819903
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Advances in Proximal Kernel Classifiers
Verlag:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2012
ISBN 10: 365927836X
ISBN 13: 9783659278365
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Zustand: New. PRINT ON DEMAND pp. 244. Bestandsnummer des Verkäufers 18128819893
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Advances in Proximal Kernel Classifiers
Verlag:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2012
ISBN 10: 365927836X
ISBN 13: 9783659278365
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Zustand: New. Print on Demand pp. 244 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. Bestandsnummer des Verkäufers 131734880
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Advances in Proximal Kernel Classifiers: Proximal Kernel Classifiers and its Application with MATLAB
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 365927836X
ISBN 13: 9783659278365
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