Abstract
Cost-sensitive specialization is a generic technique for misclassification cost sensitive induction. This technique involves specializing aspects of a classifier associated with high misclassification costs and generalizing those associated with low misclassification costs. It is widely applicable and simple to implement. It could be used to augment the effect of standard cost-sensitive induction techniques. It should directly extend to test application cost sensitive induction tasks. Experimental evaluation demonstrates consistent positive effects over a range of misclassification cost sensitive learning tasks.
Original language | English |
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Title of host publication | PRICAI 1996 |
Subtitle of host publication | Topics in Artificial Intelligence - 4th Pacific Rim International Conference on Artificial Intelligence, Proceedings |
Editors | Norman Foo, Randy Goebel |
Publisher | Springer |
Pages | 23-34 |
Number of pages | 12 |
ISBN (Print) | 3540615326, 9783540615323 |
DOIs | |
Publication status | Published - 1 Jan 1996 |
Externally published | Yes |
Event | Pacific Rim International Conference on Artificial Intelligence 1996 - Cairns, Australia Duration: 26 Aug 1996 → 30 Aug 1996 Conference number: 4th https://link.springer.com/book/10.1007/3-540-61532-6 (Proceedings) |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 1114 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | Pacific Rim International Conference on Artificial Intelligence 1996 |
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Abbreviated title | PRICAI 1996 |
Country/Territory | Australia |
City | Cairns |
Period | 26/08/96 → 30/08/96 |
Internet address |
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