An Implementation of Several Approaches to Utility-Based
Learning for Both Classification and Regression Tasks
Description
Provides a set of functions that can be used to obtain better predictive performance on cost-sensitive and cost/benefits tasks (for both regression and classification). This includes re-sampling approaches, cost-based methods, special purpose evaluation metrics as well as specific learning systems.