Timeline for Convert back standardized linear predictor
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 7, 2013 at 11:41 | vote | accept | Rob | ||
| Jul 16, 2013 at 13:18 | vote | accept | Rob | ||
| Aug 7, 2013 at 11:41 | |||||
| Jul 12, 2013 at 11:39 | answer | added | Rob | timeline score: 2 | |
| Jul 12, 2013 at 9:55 | comment | added | Peter Flom | oh, OK, you didn't mention you used boosting. That makes more sense. I don't have an answer to your question, but there may be one. | |
| Jul 11, 2013 at 23:19 | comment | added | Rob | @PeterFlom The approach that I used (boosting) has some advantages over other regression techniques. The purpose of the final model is (absolute risk) prediction so for that the standardization is not a problem, but in my paper I would like to present the models way that is not too complicated. | |
| Jul 11, 2013 at 23:11 | comment | added | Peter Flom | Yes, I realize that. But if you want the output in unstandardized form, then why not run a regression that does that? | |
| Jul 11, 2013 at 23:10 | comment | added | Rob | @PeterFlom I used a regularized regression approach in which the variables are automatically standardized. | |
| Jul 11, 2013 at 23:06 | comment | added | Peter Flom | Why not just run the model on the unstandardized variables to start with? | |
| Jul 11, 2013 at 23:00 | history | edited | Rob |
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| Jul 11, 2013 at 22:50 | history | asked | Rob | CC BY-SA 3.0 |