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Found 6 papers, 4 papers with code
Algorithms to estimate Shapley value feature attributions
Based on the various feature removal approaches, we describe the multiple types of Shapley value feature attributions and methods to calculate each one.
Explaining a Series of Models by Propagating Shapley Values
Local feature attribution methods are increasingly used to explain complex machine learning models.
Explainable AI for Trees: From Local Explanations to Global Understanding
3) A new set of tools for understanding global model structure based on combining many local explanations of each prediction.
Consistent Individualized Feature Attribution for Tree Ensembles
A unified approach to explain the output of any machine learning model.
Anesthesiologist-level forecasting of hypoxemia with only SpO2 data using deep learning
We also provide a simple way to visualize the reason why a patient's risk is low or high by assigning weight to the patient's past blood oxygen values.
Consistent feature attribution for tree ensembles
Note that a newer expanded version of this paper is now available at: arXiv:1802. 03888 It is critical in many applications to understand what features are important for a model, and why individual predictions were made.
