creators_name: Turney, Peter type: confpaper datestamp: 2001-09-17 lastmod: 2011-03-11 08:54:48 metadata_visibility: show title: Types of cost in inductive concept learning ispublished: unpub subjects: comp-sci-art-intel subjects: comp-sci-mach-learn subjects: comp-sci-stat-model full_text_status: public keywords: cost, learning, misclassification error, inductive concept learning, complexity, cost-sensitive learning. 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. 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