Multidamage Detection of Bridges Using Rough Set Theory and Naive-Bayes Classifier

Bayes and Naive Bayes Classifier

Bayes and Naive-Bayes Classifier

Pairwise Naive Bayes Classifier

Improving Naive Bayes Classifier Using Conditional Probabilities

Naive Bayes classifier is the simplest among Bayesian Network classifiers. It has shown to be very efficient on a variety of data classification problems. However, the strong assumption that all features are conditionally independent given the class is often violated on many real world applications. Therefore, improvement of the Naive Bayes classifier by alleviating the feature independence ass...

Outlier Detection Using Rough Set Theory

In this paper, we suggest to exploit the framework of rough set for detecting outliers — individuals who behave in an unexpected way or feature abnormal properties. The ability to locate outliers can help to maintain knowledge base integrity and to single out irregular individuals. First, we formally define the notions of exceptional set and minimal exceptional set. We then analyze some special...

The Indifferent Naive Bayes Classifier

The Naive Bayes classifier is a simple and accurate classifier. This paper shows that assuming the Naive Bayes classifier model and applying Bayesian model averaging and the principle of indifference, an equally simple, more accurate and theoretically well founded classifier can be obtained. Introduction In this paper we use Bayesian model averaging and the principle of indifference to derive a...