@unpublished{cogprints1804, title = {Types of cost in inductive concept learning}, author = {Peter Turney}, year = {2000}, pages = {15--21}, keywords = {cost, learning, misclassification error, inductive concept learning, complexity, cost-sensitive learning.}, url = {http://cogprints.org/1804/}, abstract = {Inductive concept learning is the task of learning to assign cases to a discrete set of classes. In real-world applications of concept learning, there are many different types of cost involved. The majority of the machine learning literature ignores all types of cost (unless accuracy is interpreted as a type of cost measure). A few papers have investigated the cost of misclassification errors. Very few papers have examined the many other types of cost. In this paper, we attempt to create a taxonomy of the different types of cost that are involved in inductive concept learning. This taxonomy may help to organize the literature on cost-sensitive learning. We hope that it will inspire researchers to investigate all types of cost in inductive concept learning in more depth. } }