The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widel...

With the enormous growth of computer networks and the huge increase in the number of applications that rely on it, network security is gaining increasing importance. Moreover, almost all computer systems suffer from security vulnerabilities which are both technically difficult and economically costly to be solved by the manufacturers. Therefore, the role of Intrusion Detection Systems (IDSs), a...

Background: Exposures are occasionally only available in an aggregated form, such as an average physical exposure for each job title. When quantifying the relationship between an individual level outcome and a group level exposure, the variance estimates are contaminated with Berkson measurement error. If the aggregated exposures come from a separate sample, such as a job exposure matrix, the a...

Bayesian networks are popular in the classification literature. The simplest kind of Bayesian network, i.e. naïve Bayesian network, has gained the interest of many researchers because of quick learning and inferring. However, when there are lots of classes to be inferred from a similar set of evidences, one may prefer to have a united network. In this paper we present a new method for merging n...

This paper improves the naïve bayesian classification algorithm , combining with the rough set theory we can get a naive bayesian classifier algorithm based on the rough set. We implement this algorithm on a cloud platform using map-reduce programming mode and get a excellent result. A recall rate of 76.4 was achieved when classifying Tibetan Web pages .

OBJECTIVE: To classify patients by age based upon information extracted from their electro-cardiograms (ECGs). To develop and compare the performance of Bayesian classifiers. METHODS AND MATERIAL: We present a methodology for classifying patients according to statistical features extracted from their ECG signals using a genetically evolved Bayesian network classifier. Continuous signal feature...

Bayesian classifier has gained wide popularity as a probability-based classification method despite its assumption that attributes are conditionally mutually independent given the class label. This paper makes a study into various algorithms to improve the classification accuracy of Bayesian methods with respect to real estate datasets. We have applied Bayesian methods on two variations of data...