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Results tagged with cross-validation
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user 45264
Refers to general procedures that attempt to determine the generalizability of a statistical result. Cross-validation arises frequently in the context of assessing how a particular model fit predicts future observations. Methods for cross-validation usually involve withholding a random subset of the data during model fitting and quantifying how accurate the withheld data are predicted and repeating this process to get a measure of prediction accuracy.
3
votes
Training with a subset of data: relationship between subset size and training metric?
Do I understand correctly from your test RMSE, that the error is lower as you increase the size of your fraction used in training?
If you do 5-fold cross validation using a fraction of 0.01, that imp …
- 15.1k
1
vote
Accepted
What is the best way to visualize 10 Fold Cross Validation Scores?
Do you only have one single model? If you were only mixing the data up (and not trying different parameter values) then any plot might not be very really useful. If performance is on the y-axis, what …
- 15.1k
9
votes
Accepted
Stratify on regression
I have done this before and didn't find a default implementation - the StratifiedKFold and RepeatedStratifiedKFold are only documented to work with classes.
The way I ended up doing it was not quite …
- 15.1k