Using Fuzzy Clustering to Improve Naive Bayes Classifiers and Probabilistic Networks

Probabilistic Networks and Fuzzy Clustering as Generalizations of Naive Bayes Classifiers

Although at first sight probabilistic networks and fuzzy clustering seem to be disparate areas of research, a closer look reveals that they can both be seen as generalizations of naive Bayes classifiers. If all attributes are numeric (except the class attribute, of course), naive Bayes classifiers often assume an axis-parallel multidimensional normal distribution for each class as the underlyin...

Using Fuzzy Clustering to Improve Naive Bayes Classi ers and Probabilisti Networks

Improving Naive Bayes Classifiers Using Neuro-Fuzzy Learning

Naive Bayes classifiers are a well-known and powerful type of classifiers that can easily be induced from a dataset of sample cases. However, the strong conditional independence and distribution assumptions underlying them can sometimes lead to poor classification performance. Another prominent type of classifiers are neuro-fuzzy classification systems, which derive (fuzzy) classifiers from dat...

Online Training Assessment in Virtual Reality Simulatorsbased on Fuzzy Naive Bayes

1 Ronei Marcos de Moraes, Department of Statistics, Federal University of Paraíba. Cidade Universitária s/n, Castelo Branco, João Pessoa-PB. 58.051-900. Brazil. [email protected] 2 Liliane dos Santos Machado, Department of Informatics, Federal University of Paraíba. Cidade Universitária s/n, Castelo Branco, João Pessoa-PB, Brazil. 58.051-900. [email protected] Abstract  Training systems based ...

Bayesian Network Classifiers. An Application to Remote Sensing Image Classification

Different probabilistic models for classification and prediction problems are anlyzed in this article studying their behaviour and capability in data classification. To show the capability of Bayesian Networks to deal with classification problems four types of Bayesian Networks are introduced, a General Bayesian Network, the Naive Bayes, a Bayesian Network Augmented Naive Bayes and the Tree Aug...