Timeline for Estimating the most important features in a k-means cluster partition
Current License: CC BY-SA 3.0
13 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 22, 2021 at 11:25 | comment | added | ttnphns | One of popular internal clustering criteria, Ratkowski-Lance, can evaluate the "quality" of a cluster partition on the level of each variable separately, thus measuring the contribution or importance of it. It does it on the basis of one-way ANOVA. This is an approach identical or similar to that described below by Frank. | |
| Aug 20, 2021 at 18:22 | answer | added | Yousef | timeline score: 0 | |
| Nov 2, 2019 at 15:10 | answer | added | ZillGate | timeline score: -1 | |
| Jul 14, 2017 at 14:40 | history | edited | gung - Reinstate Monica | CC BY-SA 3.0 |
added tag; light editing; removed irrelevant reference to R
|
| Sep 15, 2014 at 20:18 | answer | added | Gyan Veda | timeline score: 8 | |
| Nov 26, 2013 at 7:26 | history | edited | ttnphns | CC BY-SA 3.0 |
added 9 characters in body; edited title
|
| Nov 26, 2013 at 2:01 | comment | added | Franck Dernoncourt | Thanks for the clarification. One usual term to designate this issue in machine learning is feature selection. | |
| Nov 26, 2013 at 1:58 | vote | accept | user1624577 | ||
| Nov 26, 2013 at 1:51 | answer | added | Franck Dernoncourt | timeline score: 17 | |
| Nov 26, 2013 at 1:45 | review | First posts | |||
| Nov 26, 2013 at 1:52 | |||||
| Nov 26, 2013 at 1:39 | comment | added | user1624577 | Yes the most useful is what I meant. I think part of my problem with figuring this out is how to word it. | |
| Nov 26, 2013 at 1:30 | comment | added | Franck Dernoncourt | How do you define "important/dominant"? Do you mean the most useful to discriminate between clusters? | |
| Nov 26, 2013 at 1:25 | history | asked | user1624577 | CC BY-SA 3.0 |