Title :
Fuzzy-Rough Data Reduction Based on Information Entropy
Author :
Zhao, Jun-Yang ; Zhang, Zhi-Li
Author_Institution :
Xi´´an Res. Inst. Of Hi-tech Hongqing Town, Xi´´an
Abstract :
Presently, many researches have been carried out on rough set based data reduction. However, this method encounters a problem when dealing with real-valued data and fuzzy information. By lucubrating the theory of fuzzy rough set and utilizing the definition of information entropy presented in literature [5], the information entropy model of fuzzy rough set has been constructed. Then the conditional information entropy of attributes is adopted to measure the significance of attributes. On this condition, a heuristic fuzzy-rough data reduction method based on information entropy (E-FRDR) has been put forward. Finally, the method is validated by an example that indicates the method is feasible.
Keywords :
data reduction; entropy; fuzzy set theory; rough set theory; data reduction; fuzzy set theory; information entropy; rough set theory; Algorithm design and analysis; Cities and towns; Cybernetics; Fuzzy set theory; Fuzzy sets; Information analysis; Information entropy; Machine learning; Machine learning algorithms; Set theory; Data reduction; Fuzzy rough set; Information entropy; Significance of attributes;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370792
