Results for "dataset documentation"
Structured dataset documentation covering collection, composition, recommended uses, biases, and maintenance.
Training with a small labeled dataset plus a larger unlabeled dataset, leveraging assumptions like smoothness/cluster structure.
Standardized documentation describing intended use, performance, limitations, data, and ethical considerations.
One complete traversal of the training dataset during training.
A dataset + metric suite for comparing models; can be gamed or misaligned with real-world goals.
Error due to sensitivity to fluctuations in the training dataset.
Required descriptions of model behavior and limits.
A structured collection of examples used to train/evaluate models; quality, bias, and coverage often dominate outcomes.
Differences between training and deployed patient populations.