Create DataEvaluator to quantify the value of data.

Data Evaluator#

Provides an ABC for DataEvaluator to inherit from. The work flow is as follows: Register, DataFetcher -> DataEvaluator -> exper_methods


DataEvaluator(*args, **kwargs)

Abstract class of Data Evaluators.



Mixin for DataEvaluators without a prediction model and use embeddings.

AME(*args, **kwargs)

Implementation of Average Marginal Effect Data Valuation.

DVRL(*args, **kwargs)

Data valuation using reinforcement learning class, implemented with PyTorch.

InfluenceFunction(*args, **kwargs)

Influence Function Data evaluation implementation.

InfluenceSubsample(*args, **kwargs)

Influence computed through subsamples implementation.

KNNShapley(*args, **kwargs)

Data valuation using KNNShapley implementation.

DataOob(*args, **kwargs)

Data Out-of-Bag data valuation implementation.

DataBanzhaf(*args, **kwargs)

Data Banzhaf implementation.

BetaShapley(*args, **kwargs)

Beta Shapley implementation.

DataShapley(*args, **kwargs)

Data Shapley implementation.

LavaEvaluator(*args, **kwargs)

Data valuation using LAVA implementation.

LeaveOneOut(*args, **kwargs)

Leave One Out data valuation implementation.

ShapEvaluator(*args, **kwargs)

Abstract class for all semivalue-based methods of computing data values.

RandomEvaluator(*args, **kwargs)

Completely Random DataEvaluator for baseline comparison purposes.

RobustVolumeShapley(*args, **kwargs)

Robust Volume Shapley and Volume Shapley data valuation implementation.

Sampler(*args, **kwargs)

Abstract Sampler class for marginal contribution based data evaluators.

TMCSampler(*args, **kwargs)

TMCShapley sampler for semivalue-based methods of computing data values.

GrTMCSampler(*args, **kwargs)

TMC Sampler with terminator for semivalue-based methods of computing data values.