DocumentCode :
2737604
Title :
Enterprise Financial Distress Evaluation based on Fuzzy-Rough approach
Author :
Lee, Ming-Chang
Author_Institution :
Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung
fYear :
2007
fDate :
5-7 Sept. 2007
Firstpage :
296
Lastpage :
296
Abstract :
The traditional statistical models assume the covariance matrices for two populations are identical and both populations need to be described by multivariate normal distribution. Clearly, these assumptions do not always reflect the real world. Rough set is a new technique for data mining domain application. In this study, establish a financial distress prediction model using Fuzzy-Rough approach to capture fuzzy rule form data sample. The empirical research which is based on the latest data of Taiwan s listed company, the result shows that this method is high accurate and have reinforcement learning properties and mapping capabilities.
Keywords :
covariance matrices; data mining; finance; fuzzy set theory; learning (artificial intelligence); rough set theory; statistical analysis; covariance matrices; data mining domain application; enterprise financial distress evaluation; fuzzy-rough approach; multivariate normal distribution; reinforcement learning; rough set; statistical models; Covariance matrix; Data mining; Fuzzy sets; Fuzzy systems; Gaussian distribution; Knowledge based systems; Learning; Predictive models; Rough sets; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing, Information and Control, 2007. ICICIC '07. Second International Conference on
Conference_Location :
Kumamoto
Print_ISBN :
0-7695-2882-1
Type :
conf
DOI :
10.1109/ICICIC.2007.287
Filename :
4427941
Link To Document :
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