Empirical Evaluation of a Hybrid Genetic Decision Tree Induction Algorithm Table of Contents 1. The prototypical example of the problem of cost-sensitive classification is medical diagnosis, where a doctor would like to balance the costs of various possible medical tests with the expected benefits of the tests for the patient. These are some of the questions investigated here.
Cost is domain-specific and is quantified in arbitrary units.
It is assumed here that the costs of tests are measured in the same units as the benefits of correct classification. Benefit is treated as negative cost. It is sensitive to classification error costs. It combines a greedy search heuristic with a genetic search algorithm. The problem of cost-sensitive classification arises frequently.