Fuzzy Support Vector Machines
Resource
IEEE Transactions on Neural Networks 13 (2): 464-471
Journal
IEEE Transactions on Neural Networks
Journal Volume
13
Journal Issue
2
Pages
464-471
Date Issued
2002-03
Author(s)
Lin, Chun-Fu
Abstract
A support vector machine (SVM) learns the decision surface from two distinct classes of the input points. In many applications, each input point may not he fully assigned to one of these two classes. In this paper, we apply a fuzzy membership to each input point and reformulate the SVMs such that different input points can make different contributions to the learning of decision surface. We call the proposed method fuzzy SVMs (FSVMs).
SDGs
Type
journal article