Timeline for Does PCA change the values of the data?
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jul 9, 2016 at 9:39 | comment | added | Has QUIT--Anony-Mousse | Therefore, every dimensionality reduction will be lossy at some point (or not reduce dimensionality anymore). Proof complete. | |
| Jul 9, 2016 at 8:38 | comment | added | MyBushisaNeonJungle | @Anony-Mousse if we did that then there would be no data to learn from, and reducing too many dimensions may lead to subsequent overfitting. | |
| Jul 9, 2016 at 1:42 | comment | added | Has QUIT--Anony-Mousse | Of course it can cause significant loss. Any dimensionality reduction can cause loss, or we would always reduce data to 0 dimensions. | |
| Jul 8, 2016 at 23:48 | comment | added | MyBushisaNeonJungle | I have a bad habit, but I like to confirm things, so you're saying PCA does in fact changes values of data right? Does this ever cause any significant loss ever? | |
| Jul 7, 2016 at 14:17 | review | First posts | |||
| Jul 7, 2016 at 14:30 | |||||
| Jul 7, 2016 at 14:15 | history | answered | YTK | CC BY-SA 3.0 |