June Edition: Get into SHAP

The ins and outs of a powerful explainable-AI approach

The power and size of machine learning models have grown to new heights in recent years. With greater complexity comes the need for more accountability and transparency—both for the practitioners who build these models and for those who interpret their results.

Within the wide field of explainable AI, one approach that has shown great promise (and drawn a lot of attention) is SHAP (from …

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