Support Vector Machines (SVM) have been extensively studied and have shown remarkable success in many applications. However the success of SVM is very limited when it is applied to...
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for ...
Juan Luis Castro, L. D. Flores-Hidalgo, Carlos Jav...
In this paper, we investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive ...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...