Title :
Algorithms of extracting fuzzy rules from sample data
Author_Institution :
Dept. of Comput. Sci. & Applic., Zhengzhou Inst. of Aeronaut. Ind. Manage., Zhengzhou, China
Abstract :
How to extract or “mining” knowledge from mass of datum are one of research field in Data Mining. Extracting fuzzy rules from sample data through taking the advantage of neural network. According to the fuzzy method in fuzzy control technology, a fuzzy language variable be generated in mining approach. To present a bi-direction training algorithm based on BP algorithm in neural network, which depends on the training of membership function, the screening of fuzzy language, decision about the correlation between properties in the network. To tailor the correlations in trained network, and make a list of candidate rules by clustering algorithm to extract the fuzzy rules.
Keywords :
data mining; fuzzy set theory; pattern clustering; clustering algorithm; data mining; fuzzy control technology; fuzzy language; fuzzy rules extraction; mining knowledge; neural network; sample data; trained network; Classification algorithms; Employment; Filtering algorithms; Heuristic algorithms; algorithm; data mining; fuzzy rule; neural network;
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
DOI :
10.1109/ICICISYS.2010.5658802