A cost-based fuzzy system for pattern classification with class importance

This paper proposes a cost-based fuzzy classification system for pattern classification problems with an order of class importance. The task here is to minimize the misclassification of patterns from an important class. It is assumed that the classification importance is given for each class, not for each pattern. Another assumption is that only the order of importance is given for given classes without any numerical measures of importance. We show the performance of the proposed cost-based fuzzy classification system for a real-world pattern classification problem. © 2008 International Symposium on Artificial Life and Robotics (ISAROB).