Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems. In this paper, we introduce the use of SVM for multivariate fuzzy linear and nonlinear regression models. Using the basic idea underlying SVM for multivariate fuzzy regressions gives comput
✦ LIBER ✦
Fuzzy cost support vector regression on the fuzzy samples
✍ Scribed by Abedin Vahedian; Mehri Sadoghi Yazdi; Sohrab Effati; Hadi Sadoghi Yazdi
- Book ID
- 106347800
- Publisher
- Springer US
- Year
- 2010
- Tongue
- English
- Weight
- 683 KB
- Volume
- 35
- Category
- Article
- ISSN
- 0924-669X
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
Support vector fuzzy regression machines
✍
Dug Hun Hong; Changha Hwang
📂
Article
📅
2003
🏛
Elsevier Science
🌐
English
⚖ 289 KB
Fuzzy rule-based support vector regressi
✍
Ling Wang; Zhichun Mu; Hui Guo
📂
Article
📅
2005
🏛
South China University of Technology and Academy o
🌐
English
⚖ 404 KB
Support vector fuzzy adaptive network in
✍
Judong Shen; Yu-Ru Syau; E.S. Lee
📂
Article
📅
2007
🏛
Elsevier Science
🌐
English
⚖ 1008 KB
Neural-fuzzy systems have been proved to be very useful and have been applied to modeling many humanistic problems. But these systems also have problems such as those of generalization, dimensionality, and convergence. Support vector machines, which are based on statistical learning theory and kerne
A fuzzy support vector regression model
✍
Kuo-Ping Lin; Ping-Feng Pai
📂
Article
📅
2010
🏛
Elsevier Science
🌐
English
⚖ 388 KB
Regularized least squares fuzzy support
✍
Reshma Khemchandani; Jayadeva; Suresh Chandra
📂
Article
📅
2009
🏛
Elsevier Science
🌐
English
⚖ 213 KB
A New Fuzzy Support Vector Machine Based
✍
Qing Tao; Jue Wang
📂
Article
📅
2004
🏛
Springer US
🌐
English
⚖ 127 KB