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.