data requirements

reference dataset

Needs a baseline or reference dataset for comparison

8 techniques

	Goals		Models	Data Types	Description
SHapley Additive exPlanations		Algorithmic	Architecture/model Agnostic Requirements/black Box	Any	SHAP (SHapley Additive exPlanations) explains one prediction by sharing out the gap between that prediction and a...
Integrated Gradients		Algorithmic	Architecture/neural Networks Architecture/neural Networks/transformer +4	Image Tabular Text	Integrated Gradients assigns input features scores for a prediction relative to a chosen reference input, called the...
DeepLIFT		Algorithmic	Requirements/model Internals Architecture/neural Networks +2	Any	DeepLIFT (Deep Learning Important FeaTures) explains a single prediction of a neural network by dividing the difference...
Synthetic Data Evaluation		Testing	Architecture/model Agnostic Requirements/black Box	Tabular	Synthetic data evaluation checks whether an artificial dataset made to stand in for sensitive real records is safe to...
Data Validation Checks		Testing	Architecture/model Agnostic Requirements/black Box	Tabular	Data validation checks apply a written set of rules about what valid data look like to every new batch of data before a...
Kernel Two-Sample Test (Maximum Mean Discrepancy)		Algorithmic	Architecture/model Agnostic Requirements/black Box	Any	A kernel two-sample test checks whether two sets of data could have come from the same distribution; in assurance it is...
TimeSHAP		Algorithmic	Architecture/neural Networks/recurrent Requirements/black Box	Time-series	TimeSHAP explains one prediction of a model that reads a sequence of events, such as a recurrent neural network that...
Actionable Recourse Audit		Testing	Architecture/linear Models Architecture/linear Models/logistic +1	Tabular	An actionable recourse audit checks whether the people a linear classifier refuses, for example for a loan, a job...

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