Fuzzy Naive Bayesian for constructing regulated network with weights

Xi Y. Zhou, Xue W. Tian, Joon S. Lim, Feng Liu, Dong-Hoon Lee, Ricardo Lagoa, Sandeep Kumar
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
more » ... nd weights to construct a regulated network. Finally, we will classify the heart and Haberman datasets by the FNB network to compare with experiments of Naive Bayesian and TAN. The experiment results show that the FNB has a higher classification rate than Naive Bayesian and TAN.
doi:10.3233/bme-151476 pmid:26405944 fatcat:rzppazgwu5f5ljawnlb4pnyh7u