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All Outputs (8)

Development of an evolutionary cost sensitive decision tree induction algorithm (2022)
Presentation / Conference
Kassim, M., & Vadera, S. (2022, May). Development of an evolutionary cost sensitive decision tree induction algorithm. Presented at 2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA), Sabratha, Libya

This paper develops an Evolutionary Elliptical Cost-Sensitive Decision Tree Algorithm (EECSDT) which learns cost-sensitive non-linear decision trees for multiclass problems. EECSDT is developed by formulating the problem as an optimization task in wh... Read More about Development of an evolutionary cost sensitive decision tree induction algorithm.

Feature selection in meta learning framework (2014)
Presentation / Conference
Shilbayeh, S., & Vadera, S. (2014, August). Feature selection in meta learning framework. Presented at The Science and Information Conference, Science and Information Conference

Feature selection is a key step in data mining. Unfortunately, there is no single feature selection method that is always the best and the data miner usually has to experiment with different methods using a trial and error approach, which can be time... Read More about Feature selection in meta learning framework.

A multi-armed bandit approach to cost-sensitive decision tree learning (2012)
Presentation / Conference
Lomax, S., Vadera, S., & Saraee, M. (2012, December). A multi-armed bandit approach to cost-sensitive decision tree learning. Presented at 2012 IEEE 12th International Conference on Data Mining Workshops, Brussels, Belgium

Several authors have studied the problem of inducing decision trees that aim to minimize costs of misclassification and take account of costs of tests. The approaches adopted vary from modifying the information theoretic attribute selection measure u... Read More about A multi-armed bandit approach to cost-sensitive decision tree learning.

Obtaining E-R diagrams semi-automatically from natural language specifications (2004)
Presentation / Conference
Meziane, F., & Vadera, S. (2004, April). Obtaining E-R diagrams semi-automatically from natural language specifications. Poster presented at Sixth International Conference on Enterprise Information Systems (ICEIS 2004), Universidade Portucalense, Porto, Portugal

Since their inception, entity relationship models have played a central role in systems specification, analysis and development. They have become an important part of several development methodologies and standards such as SSADM. Obtaining entity r... Read More about Obtaining E-R diagrams semi-automatically from natural language specifications.

A comparison of computer science and software engineering programmes in English universities (2004)
Presentation / Conference
Meziane, F., & Vadera, S. (2004, March). A comparison of computer science and software engineering programmes in English universities. Presented at 17th Conference on Software Engineering Education and Training 2004, Norfolk, Virginia, USA

Recent years have seen much debate about the appropriate content of software engineering (SE) programs and how they relate to computer science (CS) programs, culminating in the distinguishing knowledge areas identified in the ACM/IEEE CS and SE curri... Read More about A comparison of computer science and software engineering programmes in English universities.

A web based management of references (2004)
Presentation / Conference
O'Shea, S., Saraee, M., & Vadera, S. (2004, January). A web based management of references. Presented at The 2004 International Research Conference on Innovations in Information Technology (IIT2004), Dubai, UAE, Dubai, UAE

During the evolution of research from the beginning of a project to the end a large amount of information is accumulated from books, journals, articles, manuals and the internet. Managing all this information is a complex and crucial part, especially... Read More about A web based management of references.

Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification (2000)
Presentation / Conference
Ambrosiadou, B., Vadera, S., Shankararaman, V., & Goulis, D. (2000, May). Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification. Presented at Proc of the ICSC Symposium on Neural Computation, Berlin, Germany

Diabetes mellitus is now recognised as a major worldwide public health problem. At present, about 100 million people are registered as diabetic patients. Many clinical, social and economic problems occur as a consequence of insulin-dependent diab... Read More about Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification.

Any time probabilistic reasoning for sensor validation (1998)
Presentation / Conference
Ibarguengoytia, P., Sucar, E., & Vadera, S. (1998, March). Any time probabilistic reasoning for sensor validation. Presented at Fourteenth Conference on Uncertainty in Artificial Intelligence, University of Wisconsin Business School, Madison, Wisconsin, USA

For many real time applications, it is important to validate the information received form the sensors before entering higher levels of reasoning. This paper presents an any time probabilistic algorithm for validating the information provided by sens... Read More about Any time probabilistic reasoning for sensor validation.