Fuzzy cost support vector regression on the fuzzy samples

Fuzzy cost support vector regression on the fuzzy samples

This paper presents a new version of support vector regression (SVR) named Fuzzy Cost SVR (FCSVR) with a unique property of operating on fuzzy data where fuzzy cost (fuzzy margin and fuzzy penalty) are maximized. This idea admits to have uncertainty in the penalty and margin terms jointly. Robustnes...

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Veröffentlicht in:Applied intelligence (Dordrecht, Netherlands) Netherlands), 2011-12, Vol.35 (3), p.428-435
Hauptverfasser: Vahedian, Abedin, Sadoghi Yazdi, Mehri, Effati, Sohrab, Sadoghi Yazdi, Hadi
Format: Artikel
Sprache:eng
Schlagworte:
Artificial Intelligence
Computer Science
Fuzzy
Fuzzy logic
Fuzzy set theory
Intelligence
Machines
Manufacturing
Mathematical analysis
Mechanical Engineering
Processes
Random variables
Regression
Robustness
Support vector machines
Vectors (mathematics)
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Beschreibung
Zusammenfassung:This paper presents a new version of support vector regression (SVR) named Fuzzy Cost SVR (FCSVR) with a unique property of operating on fuzzy data where fuzzy cost (fuzzy margin and fuzzy penalty) are maximized. This idea admits to have uncertainty in the penalty and margin terms jointly. Robustness against noise is shown to be superior in the experimental results as a property compared with conventional SVR.
ISSN:0924-669X
1573-7497
DOI:10.1007/s10489-010-0232-5