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Fuzzy Naive Bayesian for constructing regulated network with weights
2015
Bio-medical materials and engineering
In the data mining field, classification is a very crucial technology, and the Bayesian classifier has been one of the hotspots in classification research area. However, assumptions of Naive Bayesian and Tree Augmented Naive Bayesian (TAN) are unfair to attribute relations. Therefore, this paper proposes a new algorithm named Fuzzy Naive Bayesian (FNB) using neural network with weighted membership function (NEWFM) to extract regulated relations and weights. Then, we can use regulated relations
doi:10.3233/bme-151476
pmid:26405944
fatcat:rzppazgwu5f5ljawnlb4pnyh7u