Timeline for K-nearest neighbor supervised or unsupervised machine learning?
Current License: CC BY-SA 4.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jan 24, 2023 at 19:09 | comment | added | Andrea Ciufo |
On Sklearn is under supervised models, I think also for this reason can be misleading and it can create confusion with what is written in this paper
|
|
| Oct 13, 2022 at 16:51 | comment | added | haneulkim | Totally agree with you! So many answers regarding this has mostly been "supervised learning" which I do not agree with since there are no "learning" component... But I guess Approximate nearest neighboring could be seen as a clustering or supervised "machine learning" since it learns tree structure by using distances between points. | |
| May 27, 2019 at 15:21 | comment | added | Debanjan Basu | Interesting point of view -- I honestly do not know if there a canonically acceptable answer to this. But I do think that it fulfills the requirements of being an unsupervised learning program - as you add more data to it, the performance improves, indicating that there is some learning involved. Mathematically the information is saved as the connections between neighbours (and weights, where applicable). Since the number of connections grow superlinearly with number of vertices - there is definitely enough "memory" to effectively learn as new datapoints appear. Just IMO. | |
| Aug 23, 2018 at 20:32 | history | answered | Haitao Du | CC BY-SA 4.0 |