Protocol to calculate and compare exact Shapley values for different kernels in support vector machine models using binary features

The Shapley value formalism from cooperative game theory was adapted to explain predictions of machine learning models. Here, we present a protocol to calculate and compare exact Shapley values for support vector machine models with commonly used kernels and binary input features. We describe steps for installing software, preparing data, and calculating Shapley values with customizable Python scripts. We then detail procedures for analyzing results via correlation analysis and feature mapping. For complete details on the use and execution of this protocol, please refer to Roth and Bajorath.¹.