Title :
Generation of frequent fuzzy states evolution rules
Author :
Zhang, Bao-wen ; Chen, Hao-peng
Author_Institution :
Dept. of Comput. Sci., Shanghai Jiao Tong Univ., China
Abstract :
Temporal data mining is one of the important branches of data mining. A new frame of temporal data mining named fuzzy states evolution patterns discovery has been proposed in the former research. In this paper, generation of rules from discovered patterns was examined and a pruning algorithm was put forward.
Keywords :
data mining; fuzzy set theory; time series; discovered patterns; frequent fuzzy states evolution rules; pruning algorithm; temporal data mining; time series; Computer science; Cybernetics; Data mining; Electronic mail; Fuzzy sets; Joining processes; Laser sintering; Machine learning; State-space methods; Time series analysis;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1264430
