Accurate probability-based ranking of instances is crucial in many real-world data mining applications. KNN (k-nearest neighbor) [1] has been intensively studied as an effective c...
Abstract. Generally, there are two main streams of theories for studying uncertainties. One is probability theory and the other is fuzzy set theory. One of the basic ideas of fuzzy...
A naive Bayesian classifier is a probabilistic classifier based on Bayesian decision theory with naive independence assumptions, which is often used for ranking or constructing a...
Therehasbeensurprisinglylittle researchso far that systematicallyinvestigatedthe possibilityof constructinghybrid learningalgorithmsbysimplelocal modificationsto decision tree lea...
Alexander K. Seewald, Johann Petrak, Gerhard Widme...
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...