An Efficient Support Vector Machine Learning Method with Second-Order Cone Programming for Large-Scale Problems

Author： Debnath Rameswar Muramatsu Masakazu Takahashi Haruhisa

ISSN： 0924-669X

Source： Applied Intelligence, Vol.23, Iss.3, 2005-12, pp. : 219-239

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

An online incremental learning support vector machine for large-scale data

By Zheng Jun

Neural Computing & Applications, Vol. 22, Iss. 5, 2013-04 ,pp. : 1023-1035

Springer Publishing Company

Access to resources Recommend Favorite

Support vector regression with noisy data: a second order cone programming approach

By Trafalis Theodore Alwazzi Samir

International Journal of General Systems, Vol. 36, Iss. 2, 2007-04 ,pp. : 237-250

Taylor & Francis Ltd

Access to resources Recommend Favorite

Interval type-2 fuzzy weighted support vector machine learning for energy efficient biped walking

By Wang Liyang Liu Zhi Chen C. Zhang Yun

Applied Intelligence, Vol. 40, Iss. 3, 2014-04 ,pp. : 453-463

Springer Publishing Company

Access to resources Recommend Favorite

Large‐scale data mining using genetics‐based machine learning

WILEY INTERDISCIPLINARY REVIEWS: DATA MINING AND KNOWLEDGE DISCOVERY (ELECTRONIC), Vol. 3, Iss. 1, 2013-01 ,pp. : 37-61

John Wiley & Sons Inc

Access to resources Recommend Favorite

Mean field method for the support vector machine regression

By Gao J.B. Gunn S.R. Harris C.J.

Neurocomputing, Vol. 50, Iss. unknown, 2003-01 ,pp. : 391-405

Elsevier

Access to resources Recommend Favorite