All Outputs (2)

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.

Cost-sensitive Bayesian network learning using sampling (2014)
Book Chapter
Nashnush, E., & Vadera, S. (2014). Cost-sensitive Bayesian network learning using sampling. In Recent Advances on Soft Computing and Data Mining (467-476). Springer. https://doi.org/10.1007/978-3-319-07692-8_44

A significant advance in recent years has been the development of cost-sensitive decision tree learners, recognising that real world classification problems need to take account of costs of misclassification and not just focus on accuracy. The litera... Read More about Cost-sensitive Bayesian network learning using sampling.