| DOI | Resolve DOI: https://doi.org/10.1007/978-3-540-68125-0_4 |
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| Author | Search for: Holte, Robert C.; Search for: Drummond, Chris1 |
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| Affiliation | - National Research Council Canada. NRC Institute for Information Technology
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| Format | Text, Article |
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| Conference | 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, May 20-23, 2008, Osaka, Japan |
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| Subject | class distribution; cost curve; class imbalance; imbalanced dataset; credit dataset |
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| Abstract | The evaluation of classifier performance in a cost-sensitive setting is straightforward if the operating conditions (misclassification costs and class distributions) are fixed and known. When this is not the case, evaluation requires a method of visualizing classifier performance across the full range of possible operating conditions. This talk outlines the most important requirements for cost-sensitive classifier evaluation for machine learning and KDD researchers and practitioners, and introduces a recently developed technique for classifier performance visualization – the cost curve – that meets all these requirements. |
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| Publication date | 2008 |
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| Publisher | Springer |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 23002093 |
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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 | 437647c7-d5a9-4ade-843b-bd067de22e0c |
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| Record created | 2017-08-14 |
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| Record modified | 2023-11-02 |
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