Fair Isaac Corporation
DENSITY BASED CONFIDENCE MEASURES OF NEURAL NETWORKS FOR RELIABLE PREDICTIONS

Last updated:

Abstract:

Computer-implemented systems and methods for selecting a first neural network model from a set of neural network models for a first dataset, the first neural network model having a set of predictor variables and a second dataset comprising a plurality of datapoints mapped into a multi-dimensional grid that defines one or more neighborhood data regions; applying the first neural network model on the first dataset to generate a model score for one or more datapoints in the second dataset, the model score representing an optimal fit of input predictor variables to a target variable for the set of variables of the first neural network model.

Status:
Application
Type:

Utility

Filling date:

4 May 2021

Issue date:

4 Nov 2021