held-out

Sat, 18 Jul 2026 09:38:34 +0000

Definition

A ‘held-out’ dataset consists of examples intentionally excluded from the training phase of a machine learning model. This subset is used to assess how well the model generalizes to unseen data, providing an unbiased estimate of performance. It is crucial for hyperparameter tuning and validating that the model has not merely memorized the training data, thereby helping to detect overfitting before final deployment.

Summary

Data samples reserved from the training set to evaluate model performance and prevent overfitting during development.

Data Splitting on English AI Terms Dictionary

held-out

Definition

Summary