Title : ( The probabilistic constraints in the support vector machine )
Authors: Hadi Sadoghi Yazdi , Sohrab Effati , زهرا صابری ,
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Abstract
In this paper, a new support vector machine classifier with probabilistic constrains is proposed which presence probability of samples in each class is determined based on a distribution function. Noise is caused incorrect calculation of support vectors thereupon margin can not be maximized. In the proposed method, constraints boundaries and constraints occurrence have probability density functions which it help for achieving maximum margin. Experimental results show superiority of the probabilistic constraints support vector machine (PC-SVM) relative to standard SVM.
Keywords
Probabilistic constraints; Support vector machine; Margin maximization
@article{paperid:1009382,
author = {Sadoghi Yazdi, Hadi and Effati, Sohrab and زهرا صابری},
title = {The probabilistic constraints in the support vector machine},
journal = {Applied Mathematics and Computation},
year = {2007},
volume = {194},
number = {2},
month = {June},
issn = {0096-3003},
pages = {467--479},
numpages = {12},
keywords = {Probabilistic constraints; Support vector machine; Margin maximization},
}
%0 Journal Article
%T The probabilistic constraints in the support vector machine
%A Sadoghi Yazdi, Hadi
%A Effati, Sohrab
%A زهرا صابری
%J Applied Mathematics and Computation
%@ 0096-3003
%D 2007
