Method, system, and computer program product for determining feature importance using shapley values associated with a machine learning model

WO2025166095A1PCT designated stage Publication Date: 2025-08-07VISA INTERNATIONAL SERVICE ASSOCIATION
View PDF 2 Cites 0 Cited by

Patent Information

Application Number
PCT/US2025/013927
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Priority Date
2024-02-01
Filing Date
2025-01-31
Publication Date
2025-08-07

Smart Images

  • Figure US2025013927_07082025_PF_FP_ABST
    Figure US2025013927_07082025_PF_FP_ABST
Patent Text Reader

Abstract

Methods, systems, and computer program products are provided for determining feature importance using Shapley values associated with a machine learning model. An example method includes training a classification machine learning model, performing a plurality of feature ablation procedures on the classification machine learning model using a plurality of features to provide a distribution of feature ablation outcomes, training an explainer neural network machine learning model based on the distribution of the feature ablation outcomes to provide a trained explainer neural network machine learning model, wherein the explainer neural network machine learning model is configured to provide an output that comprises a prediction of a Shapley value associated with a feature, and determining one or more Shapley values of an input feature using the explainer neural network machine learning model.
Need to check novelty before this filing date? Find Prior Art

Citation Information

Patent Citations

  • Auxiliary diagnosis and treatment system and method for cardio-pulmonary resuscitation diagnosis and treatment standard

    CN117423471A

  • Systems and methods for decomposition of non-differentiable and differentiable models

    US20190378210A1