Title :
Notice of Retraction
An efficient attribute reduction algorithm
Author :
Shuhua Teng ; Jianwei Wu ; Jixiang Sun ; Shilin Zhou ; Gangqin Liu
Author_Institution :
Coll. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, 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.
Attribute reduction is one of the core contents in the theoretical research of rough sets. However, the inefficiency of attribute reduction algorithms limits the application of rough set. In this paper, we first point out some problems existing in the significance measure of attribute. Then a new measure, that is relative discernibility degree, is presented and proven to have the monotonicity property. Finally, a simplified consistent decision table is defined, based on which an efficient attribute reduction algorithm is designed. Theoretical analysis and experimental results show the effectiveness and practicability of this algorithm on the UCI data sets.
Keywords :
decision tables; rough set theory; UCI data sets; attribute reduction algorithm; consistent decision table; monotonicity property; rough sets; theoretical research; Algebra; Algorithm design and analysis; Data mining; Educational institutions; Educational technology; Information systems; Partitioning algorithms; Rough sets; Set theory; Sorting; attribute importance; attribute reduction; distinguishability; rough set;
Conference_Titel :
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-5845-5
DOI :
10.1109/ICACC.2010.5486877
