Fair Isaac Corporation
FAST AUTOMATIC EXPLANATION OF SCORED OBSERVATIONS

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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