Timeline for Kmeans - Does removing outliers on a dimension affect other dimensions clustering prediction?
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jul 17, 2018 at 17:39 | comment | added | Hohenheimsenberg | I removed 5, only those points that appeared on 2 or more features. | |
| Jul 16, 2018 at 18:13 | comment | added | Has QUIT--Anony-Mousse | 440 is tiny (in particular once you split this into k clusters), and 20 can have quite some effect. With lots of data I meant 100.000 for example. | |
| Jul 16, 2018 at 15:55 | comment | added | Hohenheimsenberg | You are right, I have 440 points and only removing 20. It's a small percentage that probably won't affect the outcome negatively. | |
| Jul 16, 2018 at 15:54 | vote | accept | Hohenheimsenberg | ||
| Jul 14, 2018 at 7:26 | history | answered | Has QUIT--Anony-Mousse | CC BY-SA 4.0 |