Timeline for is k-means generalizable at any distance? [duplicate]
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Sep 5, 2020 at 15:28 | history | closed |
ttnphns whuber♦ |
Duplicate of Why does k-means clustering algorithm use only Euclidean distance metric? | |
| Sep 5, 2020 at 11:33 | review | Close votes | |||
| Sep 5, 2020 at 15:28 | |||||
| Sep 5, 2020 at 11:18 | comment | added | ttnphns | This sort of question has bern asked multiple times here. Search the site, for example "k-means distance". | |
| Sep 5, 2020 at 11:14 | comment | added | ttnphns | Distance between what and what? Between data points or between a data point and a cluster centre? | |
| Sep 2, 2020 at 19:40 | history | edited | gunes |
edited tags
|
|
| Sep 2, 2020 at 19:40 | answer | added | gunes | timeline score: 1 | |
| Sep 2, 2020 at 13:13 | comment | added | pedro colombino | I am looking for a general theoretical framework of the applicability of k-means over any distance while allowing k-means to converge. | |
| Sep 2, 2020 at 13:10 | comment | added | user2974951 | Just to be clear, you can do it, however you will probably have to implement it yourself. I don't know of any which will let you choose. | |
| Sep 2, 2020 at 12:57 | comment | added | pedro colombino | Is it possible to choose any distance while setting the arithmetic mean as a choice in the second step? | |
| Sep 2, 2020 at 12:54 | comment | added | user2974951 | Yes, you can use any distance metric that you prefer. Although you should be able to explain why you chose that particular metric. | |
| Sep 2, 2020 at 12:51 | history | asked | pedro colombino | CC BY-SA 4.0 |