Cross-validation with Confidence
Neyman Seminar
Apr 26, 2017, 04:00 PM - 05:00 PM | 1011 Evans Hall | Happening As Scheduled
Jing Lei, Department of Statistics, CMU
Cross-validation is one of the most popular model selection methods
in statistics and machine learning. Despite its wide applicability,
traditional cross-validation methods tend to overfit, unless the ratio
between the training and testing sample sizes is very small.
We argue that such an overfitting tendency of cross-validation
is due to the ignorance of the uncertainty in the testing...