Timeline for Training with unlabeled data and the probability of correct classification
Current License: CC BY-SA 4.0
4 events
| when toggle format | what | by | license | comment | |
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| Nov 29, 2022 at 10:48 | comment | added | Daniel Lerch | (1) Yes, the second classifier is able to predict what the first classifier's performance will be for a given testing set without using the labels. (3) yes, no luck at the moment. (2) This is something I want to try, although I wanted to know if there was a common procedure for this kind of problem. | |
| Nov 29, 2022 at 8:58 | comment | added | Stephan Kolassa | (1) Are you sure your second classifier is better than random? If one class appears in 70% of cases, and classifier A always classifies as this class, then classifier B can always respond "correct" and would be right 70% of times. (2) What comes to mind is using a third classifier that uses the features, and the outputs from both original classifiers. (3) Have you thought about probabilistic classification? | |
| Nov 29, 2022 at 8:48 | history | edited | Daniel Lerch | CC BY-SA 4.0 |
added 1 character in body
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| Nov 29, 2022 at 8:40 | history | asked | Daniel Lerch | CC BY-SA 4.0 |