Implementing a Model Agnostic Framework to Provide Shapley Values Associated With a Machine Learning Model

原文（中文）

Methods, systems, and computer program products are provided for implementing a model agnostic framework to provide Shapley values associated with a machine learning model. A method may include receiving an executable file for a neural network machine learning model, converting a format of the executable file for the neural network machine learning model to an agnostic model format to provide an agnostic model format file for the neural network machine learning model, parsing the agnostic model format file, to provide a forward symbolic graph associated with the neural network machine learning model and a backward symbolic graph associated with the neural network machine learning model, receiving a real-time inference request, and determining an output of the neural network machine learning model associated with the real-time inference request and one or more Shapley values associated with the output of the neural network machine learning model.