| Download | - View accepted manuscript: Types of Cost in Inductive Concept Learning (PDF, 523 KiB)
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| Author | Search for: Turney, Peter1 |
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| Affiliation | - National Research Council of Canada. NRC Institute for Information Technology
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| Format | Text, Article |
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| Conference | Proceedings of the Cost-Sensitive Learning Workshop at the 17th ICML-2000 Conference, July 2, 2000., Stanford, California, USA |
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| 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. |
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| Publication date | 2000 |
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| Language | English |
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| NRC number | NRCC 43671 |
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| NPARC number | 5755274 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 88be18fa-23f3-47bf-a765-057e2dcf7bb8 |
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| Record created | 2008-12-02 |
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| Record modified | 2020-03-26 |
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