Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with resampling
Search options not deleted
user 27025
Resampling is taking a sample from a sample. Common uses are jackknifing (taking a subsample, eg all values but 1) & bootstrapping (sampling w/ replacement). These techniques can provide a robust estimate of a sampling distribution when it would be difficult or impossible to derive analytically.
2
votes
2
answers
4k
views
What are RMSE SD and Rsquared SD metrics in resampling results using R package:caret?
When resampling regression models, I get the traditional RMSE and Rsquared metrics, but also RMSE SD and Rsquared SD, for which I haven't found explanation in the manuals or documentations. … : Cross-Validated (2 fold)
Summary of sample sizes: 254, 252
Resampling results
RMSE Rsquared RMSE SD Rsquared SD
4.91 0.721 0.202 0.00304
Cheers
Maria …
- 127