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Bayesian network is an uncertainty inference network based on probability. Its structure learning is one of the main research techniques in the field of data mining and knowledge discovering, while constructing Bayesian network structures from data is NP hard. According to the information theory and conditional independence test, a new algorithm is presented for the construction of optimal Bayesian...
The partition clustering problem is the one of the hardest problems in nowadays research. Also Partition clustering problem is the basic problem in data mining. In most cases, the partition clustering algorithm is NP problem. In this paper, there introduced an algorithm to solve partition clustering problem in polynomial time by using some reduction technology. This algorithm is availability after...
In credibility theory, variance is usually used as a measure of the variation of a possibility distribution about the expected value. Since the variance is defined via nonlinear fuzzy integral, its computation is difficult for general fuzzy variables. To avoid this difficulty, this paper defines the spread of a fuzzy variable based on Lebesgue-Stieltjes (L-S) integral. Our approach is to find an "average...
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