Stopping criteria indicate when to exit the active learning loop.
- :py
~small_text.stopping_criteria.base.DeltaFScore
- :py
~small_text.stopping_criteria.change.ClassificationChange
- :py
~small_text.stopping_criteria.kappa.KappaAverage
- :py
~small_text.stopping_criteria.uncertainty.OverallUncertainty
- :py
~small_text.stopping_criteria.utility.MaxIterations
This interface is one of the trickiest, since you might stop on any information available within the active learning process (excluding experiment only information like the test set of course). Therefore all arguments here are optional and None
by default, and the interface only provides a very loose frame on how stopping criteria should be built.
../../small_text/stopping_criteria/base.py
For an example, see the :py~small_text.stopping_criteria.kappa.KappaAverage
, which stops when the change in the predictions over multiple iterations falls below a fixed threshold.
KappaAverage
DeltaFScore
ClassificationChange
OverallUncertainty
MaxIterations