Cross-Validation
from Wikipedia
Cross-validation, sometimes called rotation estimation, is the statistical practice of partitioning a sample of data into subsets such that the analysis is initially performed on a single subset, while the other subset(s) are retained for subsequent use in confirming and validating the initial analysis.
Common Types:
Holdout validation
Repeated random sub-sampling validation
K-fold cross-validation
Leave-one-out cross-validation
This entry was posted on Thursday, October 9th, 2008 at 2:20 pm and is filed under research.
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