Bookcover of Advances in Proximal Kernel Classifiers
Booktitle:

Advances in Proximal Kernel Classifiers

Proximal Kernel Classifiers and its Application with MATLAB

LAP LAMBERT Academic Publishing (2012-11-05 )

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ISBN-13:

978-3-659-27836-5

ISBN-10:
365927836X
EAN:
9783659278365
Book language:
English
Blurb/Shorttext:
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.
Publishing house:
LAP LAMBERT Academic Publishing
Website:
https://www.lap-publishing.com/
By (author) :
Santanu Ghorai, Anirban Mukherjee, Pranab K. Dutta
Number of pages:
244
Published on:
2012-11-05
Stock:
Available
Category:
Other
Price:
79.00 €
Keywords:
Pattern Classification, Proximal classifiers, kernel classifiers, NPPC, FRKFA, VVRKFA, regression based classification, Microarray data classification, ensemble classifiers

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