Title : ( An extension to fuzzy support vector data description-FSVDD )
Authors: Hadi Sadoghi Yazdi , yahya forghani , Sohrab Effati ,
Full TextAbstract
Fuzzy SVDD, Data description, Fuzzy numbers, Distance, Defuzzification
Keywords
, The well-known support vector data description (SVDD) is based on precise description of precise data. When we know the features of training samples precisely and we are uncertain about their class labels, the fuzzy SVDD can be used to obtain the data description. But if the features of training sam
@article{paperid:1023543,
author = {Sadoghi Yazdi, Hadi and Forghani, Yahya and Effati, Sohrab},
title = {An extension to fuzzy support vector data description-FSVDD},
journal = {Pattern Analysis and Applications},
year = {2012},
volume = {15},
number = {1},
month = {March},
issn = {1433-7541},
pages = {237--247},
numpages = {10},
keywords = {The well-known support vector data description (SVDD) is based on precise description of precise data. When we know the features of training samples precisely and we are uncertain about their class labels; the fuzzy SVDD can be used to obtain the data description. But if the features of training samples are fuzzy numbers; the fuzzy SVDD cannot be utilized. In this paper; we extend the fuzzy SVDD for the description of such training samples and then apply our proposed method; called FSVDD*; to real data. The experimental results show the ability of the proposed method in Taiwanese tea evaluation.},
}
%0 Journal Article
%T An extension to fuzzy support vector data description-FSVDD
%A Sadoghi Yazdi, Hadi
%A Forghani, Yahya
%A Effati, Sohrab
%J Pattern Analysis and Applications
%@ 1433-7541
%D 2012
