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Results tagged with cross-validation
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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.
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Cross validation techniques
What are the advantages vs disadvantages of cross validation types? Like k-fold, leave one out, etc.
- 419
15
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3
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How to choose a classifier after cross-validation?
When we do k-fold cross validation, should we just use the classifier that has the highest test accuracy? What is generally the best approach in getting a classifier from cross validation?
- 419