Prediction of S-sulfenylation sites using mRMR feature selection and fuzzy support vector machine algorithm

2018 ◽  
Vol 457 ◽  
pp. 6-13 ◽  
Author(s):  
Zhe Ju ◽  
Shi-Yun Wang
Keyword(s):  
Support Vector Machine ◽  
Feature Selection ◽  
Support Vector ◽  
Support Vector Machine Algorithm ◽  
Fuzzy Support Vector Machine

A New Fuzzy Support Vector Machine for Credit Scoring

2011 ◽  
Vol 109 ◽  
pp. 636-640
Author(s):  
Bo Tang ◽  
Min Xia
Keyword(s):  
Support Vector Machine ◽  
Economic Development ◽  
Prediction Accuracy ◽  
Credit Scoring ◽  
Fuzzy Membership ◽  
Support Vector ◽  
Good Prediction ◽  
Support Vector Machine Algorithm ◽  
Fuzzy Support Vector Machine ◽  
Good Prediction Accuracy

With China's rapid economic development, credit scoring has become very important. This paper presents a new fuzzy support vector machine algorithm used to solve the problems of credit scoring. The empirical results show that the proposed fuzzy membership model is valid ,the algorithm has good prediction accuracy and anti-noise ability.

scholarly journals A New Multi-class Fuzzy Support Vector Machine Algorithm

2014 ◽  
pp. 153-164 ◽  
Author(s):  
Friedhelm Schwenker ◽  
Markus Frey ◽  
Michael Glodek ◽  
Markus Kächele ◽  
Sascha Meudt ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Support Vector ◽  
Support Vector Machine Algorithm ◽  
Fuzzy Support Vector Machine
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