Confidence calibration for systems with cascaded predictive models
AssigneeSRI International
InventorsYunye Gong, Yi Yao, Xiao Lin, Ajay Divakaran
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AssigneeSRI International
InventorsYunye Gong, Yi Yao, Xiao Lin, Ajay Divakaran
Estimating the term…
In general, techniques are described that address the limitations of existing conformal prediction methods for cascaded models. In an example, a method includes receiving a first validation data set for validating performance of an upstream model of the two or more cascaded models and receiving a second validation data set for validating performance of a downstream model of the two or more cascaded models wherein the second validation data set is different than the first validation set; estimating system-level errors caused by predictions of the upstream model based on the first validation data set; estimating system-level errors caused by predictions of the downstream model based on the second validation data set; and generating a prediction confidence interval that indicates a confidence for the system based on the system-level errors caused by predictions of the upstream model and based on the system-level errors caused by predictions of the downstream model.
A method for determining confidence for a system having two or more cascaded models, the method comprising:
A computing system for determining confidence for a system having two or more cascaded models, the computing system comprising:
A method for determining confidence for a system having two or more cascaded models, the method comprising:
Non-transitory computer-readable storage media having instructions for determining confidence for a system having two or more cascaded models, the instructions configured to cause processing circuitry to:
Dependencies are inferred from the claim text.