Title :
A Novel Approach of Rough Set-Based Attribute Reduction Using Fuzzy Discernibility Matrix
Author :
Yang, Ming ; Chen, Songcan ; Yang, Xubing
Author_Institution :
Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
Abstract :
Rough set approach is one of effective attribute reduction (also called a feature selection) methods that can preserve the meaning of the attributes(features). However, most of existing algorithms mainly aim at information systems or decision tables with discrete values. Therefore, in this paper, we introduce a novel rough set-based method followed by establishing a fuzzy discernibility matrix by using distance preserving strategy for attribute reduction, and only choose fisher discriminant analysis with kernels as discriminant criteria for testing the effectiveness of selected attribute subsets with relatively higher fitness values, since the proposed method is independent of post-analysis algorithms (predictors). Experimental results show that the classifiers developed using the selected attribute subsets have better or comparable performance on all eight UCI benchmark datasets than those obtained by all attributes. Thus, our newly developed method can, in most cases, get effective attribute subsets. In addition, this method can be directly incorporated into other learning algorithms, such as PCA, SVM and etc. and can also be more easily applied to many real applications, such as web categorization, image recognition and etc.
Keywords :
decision tables; feature extraction; fuzzy set theory; matrix algebra; rough set theory; statistical analysis; Fisher discriminant analysis; attribute reduction; decision table; distance preserving strategy; feature selection; fuzzy discernibility matrix; information systems; post-analysis algorithm; rough set-based attribute reduction; Algorithm design and analysis; Computer science; Fuzzy sets; Image recognition; Information systems; Kernel; Prediction algorithms; Principal component analysis; Support vector machines; Testing;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.97