Timeline for Can you use discriminant analysis to classify new observations into categories generated by a previous $k$-means clustering?
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Apr 13, 2017 at 12:44 | history | edited | CommunityBot |
replaced http://stats.stackexchange.com/ with https://stats.stackexchange.com/
|
|
| Jul 5, 2012 at 16:58 | vote | accept | JEquihua | ||
| Jul 3, 2012 at 5:46 | comment | added | ttnphns | Just one general way to assess the reliability of classification is to split one big sample into one training and several test subsamples, to see how much less correctly the classifier behaves in test subsamples compared to the training one. | |
| Jul 3, 2012 at 4:16 | comment | added | JEquihua | I was kind of aware of this but... I'm not sure how to measure the reliability of the classification. I can trying agasint the already classified data to see how well it goes but ... on new data? how can I know it will work well, in which cases? | |
| Jun 30, 2012 at 5:50 | history | answered | ttnphns | CC BY-SA 3.0 |