Development of new cost-sensitive Bayesian network learning algorithms
Bayesian networks are becoming an increasingly important area for research and have been proposed for real world applications such as medical diagnoses, image recognition, and fraud detection. In all of these applications, accuracy is not sufficient alone, as there are costs involved when errors occ...
Main Author: | Nashnush, E. |
---|---|
Published: |
University of Salford
2016
|
Subjects: | |
Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.680493 |
Similar Items
-
Cost-sensitive decision tree learning using a multi-armed bandit framework
by: Lomax, S. E.
Published: (2013) -
Bayesian network structure learning using characteristic properties of permutation representations with applications to prostate cancer treatment
by: Regnier-Coudert, Olivier
Published: (2013) -
Nature of the learning algorithms for feedforward neural networks
by: Perez-Minana, Elena
Published: (1997) -
Pattern recognition in physiological time-series data using Bayesian neural networks
by: Howells, Timothy Paul
Published: (2003) -
Improved sequential and batch learning in neural networks using the tangent plane algorithm
by: May, Paul
Published: (2012)