Instance-dependent cost-sensitive learning: do we really need it?
| dc.contributor.author | Vanderschueren, Toon | |
| dc.contributor.author | Verbeke, Wouter | |
| dc.contributor.author | Baesens, Bart | |
| dc.contributor.author | Verdonck, Tim | |
| dc.date.accessioned | 2021-12-24T17:30:43Z | |
| dc.date.available | 2021-12-24T17:30:43Z | |
| dc.date.issued | 2022-01-04 | |
| dc.description.abstract | Traditionally, classification algorithms aim to minimize the number of errors. However, this approach can lead to sub-optimal results for the common case where the actual goal is to minimize the total cost of errors and not their number. To address this issue, a variety of cost-sensitive machine learning techniques has been suggested. Methods have been developed for dealing with both class- and instance-dependent costs. In this article, we ask whether we really need instance-dependent rather than class-dependent cost-sensitive learning? To this end, we compare the effects of training cost-sensitive classifiers with instance- and class-dependent costs in an extensive empirical evaluation using real-world data from a range of application areas. We find that using instance-dependent costs instead of class-dependent costs leads to improved performance for cost-sensitive performance measures, but worse performance for cost-insensitive metrics. These results confirm that instance-dependent methods are useful for many applications where the goal is to minimize costs. | |
| dc.format.extent | 9 pages | |
| dc.identifier.doi | 10.24251/HICSS.2022.191 | |
| dc.identifier.isbn | 978-0-9981331-5-7 | |
| dc.identifier.uri | http://hdl.handle.net/10125/79523 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Proceedings of the 55th Hawaii International Conference on System Sciences | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Fairness in Algorithmic Decision Making | |
| dc.subject | class-dependent | |
| dc.subject | classification | |
| dc.subject | cost-sensitive learning | |
| dc.subject | instance-dependent | |
| dc.title | Instance-dependent cost-sensitive learning: do we really need it? | |
| dc.type.dcmi | text |
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