Statistics Model selection Concept
Cross-validation
Summary
Cross-validation estimates how well a fitted model predicts new data by repeatedly fitting it on part of the data and testing it on the rest. Each observation is used for testing exactly once, with a model that did not see it. It is the standard tool to choose tuning parameters, such as a bandwidth or a penalty, and to compare predictive models.
Further reading
About this page
| Tag | HA1KJ3B9DX |
|---|---|
| URI | m2://HA1KJ3B9DX |
| Kind | concept |
| Writing | W0 stub |
| MSC | 62G09, 62J05 |
| Same as |
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