Cost-Sensitive Bayesian Network algorithm

1
Cost-Sensitive Bayesian Network algorithm
Eman Nashnush E.Nashnush1_at_edu.salford.ac.uk Unive
rsity of Salford ,Manchester, UK Sponsor in Libya
( Tripoli University )
Introduction
Machine learning algorithms are becoming an
increasingly important area for research and
application in the field of Artificial
Intelligence and data mining. One of the most
important algorithm is Bayesian network, this
algorithm have been widely used in real world
applications like medical diagnosis, image
recognition, fraud detection, and inference
problems. In all of these applications,
evaluation method as accuracy is not enough
because there are costs involve each decision.
For example, in a fraud detection application to
predict new case, there are several costs
involved when the classifier predicts a
fraudulent case as a non-fraudulent case. Also,
fraud databases have an unbalanced class
distribution which is known to affect learning
algorithms adversely. Therefore, this project
develops new algorithm that aims to minimize the
costs of prediction, misclassification, imbalance
data, time and test.