Deep SHAP is a high-speed approximation algorithm for SHAP values in deep learning models that builds on a connection withDeepLIFTdescribed in the SHAP NIPS paper. The implementation here differs from the original DeepLIFT by using a distribution of background samples instead of a single reference ...
Although it is not directly employed for inference by the model (as is the case of the coefficient of LR and SVM), it allows to measure the influence of each variable in the overall majority vote class prediction. Next, we discuss in more detail the interpretation of each algorithm. ...
Deep SHAP is a high-speed approximation algorithm for SHAP values in deep learning models that builds on a connection withDeepLIFTdescribed in the SHAP NIPS paper. The implementation here differs from the original DeepLIFT by using a distribution of background samples instead of a single reference ...