Timeline for Using SMOTE with grouped, paneled, or categorical data?
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| when toggle format | what | by | license | comment | |
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| S Jul 9 at 5:22 | history | suggested | cottontail | CC BY-SA 4.0 |
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| Jul 9 at 4:18 | review | Suggested edits | |||
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| Oct 22, 2022 at 5:51 | comment | added | Dave | Are you sure you need to use SMOTE at all? It’s really hard to recommend the best way to do something when there’s a strong argument that you shouldn’t be doing it in the first place. | |
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| Dec 11, 2019 at 11:00 | answer | added | Mehdi | timeline score: -1 | |
| Jul 8, 2017 at 10:58 | comment | added | usεr11852 | I strongly suspect one has to customise the original SMOTE algorithm to do this. Notice that distances are not well-defined between categorical variables so the concept of nearest-neighbours is murky. You could start having custom distance metrics (say some hybrid of Mahalanobis and Hamming but that a horrible exercise) My first approach would be not to use resampling to balance the dataset but actually focus on proper metrics that would adequately penalise the misclassification of minority class examples as well as classifier who do not do strong parametric assumptions. (Good basic question.) | |
| Jul 7, 2017 at 13:19 | history | asked | user1566200 | CC BY-SA 3.0 |