Non-Exhaustive Cross-Validation Task

A Non-Exhaustive Cross-Validation Task is a Cross-Validation Task in which not all the ways of splitting samples are computed.

• Context:
  • It can be solved by a Non-Exhaustive Cross-Validation System that implements a Non-Exhaustive Cross-Validation Algorithm.
• Example(s):
  • a K-Fold Cross-Validation Task,
  • a Holdout Cross-Validation Task,
  • a Monte Carlo Cross-Validation Task,
  • …
• Counter-Example(s):
  • an Exhaustive Cross-Validation Task,
  • a Nested Cross-validation Task.
• See: Temporal Data Evaluation, Out-of-Sample Forecasting Experiment, Extrinsic Performance, Variance, Model Validation, Statistics, Accuracy, Predictive Modelling, Validation Set, Overfitting, Selection Bias, Partition of a Set, Statistical Sample, Data, Training Set, Sample, Stratified K-Fold Cross Validation Algorithm.

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References

2020

• (Wikipedia, 2020) ⇒ https://www.wikiwand.com/en/Cross-validation_(statistics)#/Non-exhaustive_cross-validation Retrieved:2020-2-14.
  • Non-exhaustive cross validation methods do not compute all ways of splitting the original sample. Those methods are approximations of leave-p-out cross-validation.

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