Techniqueintro
Cross-validation
Also called k-fold cross-validation, leave-one-out.
Estimate generalization error by repeatedly training and testing on data splits.
Estimate generalization error by repeatedly training and testing on data splits.
About this page
The build computes these levels from the evidence in the repository. Each row says what the next level needs. Read what the levels mean.
| Ladder | Level | What the next level needs |
|---|---|---|
| Human proof | H0 no proof |
|
| Lean | L0 no Lean part |
|
| Visual | V0 none |
|
| Writing | W0 stub |
|
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