Quite a large update with a renewed experience for researchers: Experiment API.
Nonetheless, production users will benefit from EPIG, the new SotA in Active Learning!
Experiment API
The new experiment object will simplify your experiments by reducing it to a 1-liner.
EPIG
Contribution from @reeshipaul @Dref360 and @fbickfordsmith, EPIG is the new state-of-the-art in Bayesian Active Learning.
It better estimates the predictive uncertainty than PowerBALD and considers the labeled training set.
Stopping Criterion
A new object that helps you stop an experiment when reaching your labeling budget or a plateau in uncertainty/performance.
Breaking Changes
- Arguments in
ModelWrapper.*_on_dataset
have been for the most part moved toTrainingArguments
and are included inModelWrapper
constructor. Visit the documentation for more details.
What's Changed
- Add Stopping Criteria for loop by @Dref360 in #286
- Add EPIG by @reeshipaul @Dref360 @fbickfordsmith in #293
- Add Args to ModelWrapper to simplify common API by @Dref360 in #294
- Add documentation for criterion by @Dref360 in #297
- Experiment API v2 by @Dref360 in #296
Full Changelog: v1.9.2...v2.0.0