All Outputs (3)

Learning cost-sensitive Bayesian networks via direct and indirect methods (2016)
Journal Article
Nashnush, E., & Vadera, S. (2017). Learning cost-sensitive Bayesian networks via direct and indirect methods. Integrated Computer-Aided Engineering, 24(1), 17-26. https://doi.org/10.3233/ICA-160514

Cost-Sensitive learning has become an increasingly important area that recognizes that real world classification problems need to take the costs of misclassification and accuracy into account. Much work has been done on cost-sensitive decision tree l... Read More about Learning cost-sensitive Bayesian networks via direct and indirect methods.

Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings (2016)
Book
(2016). E. Metais, F. Meziane, M. Saraee, V. Sugumaran, S. Vadera, E. Métais, …S. Vadera (Eds.), Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings. Springer. https://doi.org/10.1007/978-3-319-41754-7

This volume of the lecture notes in computer science (LNCS) contains the papers presented at the 21st International Conference on application of Natural Language to Information Systems, held at MediacityUK, University of Salford on the 22-24 June 201... Read More about Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings.

A cost-sensitive decision tree learning algorithm based on a multi-armed bandit framework (2016)
Journal Article
Lomax, S., & Vadera, S. (2017). A cost-sensitive decision tree learning algorithm based on a multi-armed bandit framework. Computer Journal, 60(7), 941-956. https://doi.org/10.1093/comjnl/bxw015

This paper develops a new algorithm for inducing cost-sensitive decision trees that is inspired by the multi-armed bandit problem, in which a player in a casino has to decide which slot machine (bandit) from a selection of slot machines is likely to... Read More about A cost-sensitive decision tree learning algorithm based on a multi-armed bandit framework.