Fair Isaac Corporation
FAST AUTOMATIC EXPLANATION OF SCORED OBSERVATIONS
Last updated:
Abstract:
Systems and methods for generating concise explanations of scored observations that strike good, and computationally efficient, trade-offs between rank-ordering performance and explainability of scored observations are disclosed. The systems and methods described herein for explaining scored observations are based on a framework of partial dependence functions (PDFs), multi-layered neural networks (MNNs), and Latent Explanations Neural Network Scoring (LENNS).
Status:
Application
Type:
Utility
Filling date:
11 May 2021
Issue date:
26 Aug 2021