Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with assumptions of conditional independence among features given the class, called naı̈ve Bayes, is competitive with state of the art classifiers. On this paper a new naive Bayes classifier called Interval Estimation naı̈ve Bayes is proposed. Interval Estimation naı̈ve Bayes performs on two phases. On the ...

Wheeler WC and Pickett KM (2008. Topology-Bayes versus clade-Bayes in phylogenetic analysis. Mol Biol Evol. 25:447–453.) discuss two ways of summarizing the posterior probability distribution of a Bayesian phylogenetic analysis, which they refer to as ‘‘topology-Bayes’’ and ‘‘clade-Bayes.’’ They claim that the clade-Bayes approach leads to problems such as ‘‘exaggerated clade support, inconsist...

the problem of estimating the parameter ?, when it is restricted to an interval of the form , in a class of discrete distributions, including binomial negative binomial discrete weibull and etc., is considered. we give necessary and sufficient conditions for which the bayes estimator of with respect to a two points boundary supported prior is minimax under squared log error loss function. for s...

One-class Bayes learning such as one-class Naïve Bayes and one-class Bayesian Network employs Bayes learning to build a classifier on the positive class only for discriminating the positive class and the negative class. It has been applied to anomaly detection for identifying abnormal behaviors that deviate from normal behaviors. Because one-class Bayes classifiers can produce probability score...

We consider the problem of image classification when more than one visual feature is available. In such cases, Bayes fusion offers an attractive solution by combining the results of different classifiers (one classifier per feature). This is the general form of the so-called ‘‘naive Bayes’’ approach. This paper compares the performance of Bayes fusion with respect to Bayesian classification, wh...