Title :
Reduced Convex Hulls: A Geometric Approach to Support Vector Machines [Lecture Notes]
Author :
Theodoridis, Sergios ; Mavroforakis, Michael
Author_Institution :
Athens Univ.
fDate :
5/1/2007 12:00:00 AM
Abstract :
This lecture note presents a geometric interpretation of the support vector machines (SVMs), and it introduces the reduced convex hulls (RCHs). The geometric interpretation is an alternative point of view with a clear physical meaning and paves the way for developing efficient SVM algorithms
Keywords :
geometry; support vector machines; SVM; geometric approach; reduced convex hulls; support vector machines; Cost function; Error correction; Geometry; Kernel; Lagrangian functions; Linear algebra; Pattern recognition; Signal processing algorithms; Support vector machine classification; Support vector machines;
Journal_Title :
Signal Processing Magazine, IEEE
DOI :
10.1109/MSP.2007.361610
