Probabilistic Reasoning with Naïve Bayes and Bayesian Networks

Load-Frequency Control: a GA based Bayesian Networks Multi-agent System

Bayesian Networks (BN) provides a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of load-frequency control (LFC). In practice, LFC systems use proportional-integral controllers. However since these controllers are designed using a linear model, the nonlinearities...

Decision Tree Induction 17.1 Introduction 17.2 Attribute selection measure 17.3 Tree Pruning 17.4 Extracting Classification Rules from Decision Trees 17.5 Bayesian Classification 17.6 Bayes Theorem 17.7 Naïve Bayesian Classification 17.8 Bayesian Belief Networks

A First Analysis of Qualitative Influences and Synergies

Comprehensibility is a key characteristic for learning algorithms results to be useful in Knowledge Discovery in Databases tasks. Bayesian reasoning has been usually criticized as hard to explain and understand, but achieves high performance rates with simple constructs, as happens for instance with the Naive-Bayes classifier. Our approach can be viewed as a refinement of qualitative probabilis...

A New Algorithm for Generating Situation-Specific Bayesian Networks Using Bayes-Ball Method

Multi-Entity Bayesian Network (MEBN) is an expressive first-order probabilistic logic that represents the domain using parameterized fragments of Bayesian networks. Probabilistic-OWL (PR-OWL) uses MEBN to add uncertainty support to OWL, the main language of the Semantic Web. The reasoning in MEBN is made by the construction of a Situation-Specific Bayesian Network (SSBN), a minimal Bayesian net...

Classification Using Naïve Bayes- a Survey

Classification, particularly Text Classification, is a supervised learning approach categorizing into various categories, the available training set of correctly identified observations analyzed into a set of features. There are many phases involved in classification. The main classification phase involves the use of classification algorithms or classifiers. Among the various classifiers, the N...