Title :
Notice of Retraction
A selection methods of feature attributes based on RS-SVM
Author :
Gonglong Duan ; Peng Liu ; Runsheng Liu ; Long Wei
Author_Institution :
Sch. of Econ. & Manage., Xi´an Univ. of Technol., Xi´an, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In the pattern recognition system, when selecting the optimal set of attributes, we need a lot of features from the screening properties, so often there will be omissions, therefore, to use the rough set (RS) on the support vector machine (SVM) for encapsulation method of screening set of attributes, the use of RS and SVM to find the optimal combination of the characteristics of attribute combinations.
Keywords :
pattern recognition; rough set theory; support vector machines; RS-SVM; attribute combination; encapsulation method; feature attributes; optimal set selection; pattern recognition system; rough set; screening properties; screening set; support vector machine; Accuracy; Classification algorithms; Data models; Decision making; Kernel; Support vector machines; Training; encapsulate; feature attributes; rough sets (RS); support vector machine (SVM);
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-2130-4
DOI :
10.1109/ICNC.2012.6234532
