We generate and compare three types of explanations of Machine Learning predictions: simple, conservative and unifying. Simple explanations are concise, conservative explanations address the surprisingness of a prediction, and unifying explanations convey the extent to which an ML model’s predictions are applicable.
Funding
Explaining the outcomes of complex computational models