Timeline for Anomaly Detection
Current License: CC BY-SA 4.0
21 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 21, 2023 at 7:01 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Jun 21, 2023 at 21:04 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Feb 18, 2023 at 5:06 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Oct 11, 2022 at 11:08 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Jun 10, 2022 at 0:09 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| May 8, 2022 at 17:42 | answer | added | Ralph Winters | timeline score: 1 | |
| May 8, 2022 at 17:06 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Dec 30, 2021 at 8:02 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Aug 31, 2021 at 0:03 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| May 1, 2021 at 15:05 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Mar 23, 2021 at 12:48 | answer | added | 10xAI | timeline score: 1 | |
| Mar 22, 2021 at 20:13 | comment | added | saurav kumar singh | @10xAI V1:[100, 120, 15000], 15000 is for the other it would be none... | |
| Mar 22, 2021 at 17:07 | comment | added | saurav kumar singh | @NikosM. All Vendors arent typical. your 1st point is what I intend to implement but facing issues with the out put that's being generated | |
| Mar 21, 2021 at 14:26 | comment | added | 10xAI |
How do you define unusual? { V1:[100, 120, 15000], V2:[15000, 16000, 14000] }. Which one is unusual high out of the two examples?
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| Mar 21, 2021 at 10:31 | comment | added | Nikos M. | Else if all vendors are typical you can drop the vendor ID altogether and simply model all invoices together (since if vendors dont differ significantly, they are all "typical", then same rules apply to all) | |
| S Mar 21, 2021 at 5:04 | history | suggested | Nikos M. | CC BY-SA 4.0 |
format code, format text, correct spelling
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| Mar 20, 2021 at 19:56 | comment | added | WBM | Why doesn't a simple threshold based model work here (e.g. >100 invoices will be flagged as anomalous)? | |
| Mar 20, 2021 at 19:35 | comment | added | Nikos M. | maybe split data by vendor and create vendor-specific iForests? | |
| Mar 20, 2021 at 19:31 | review | Suggested edits | |||
| S Mar 21, 2021 at 5:04 | |||||
| Mar 20, 2021 at 15:27 | review | First posts | |||
| Mar 20, 2021 at 17:42 | |||||
| Mar 20, 2021 at 15:24 | history | asked | saurav kumar singh | CC BY-SA 4.0 |