Patent ID: 11880432
Assignee: KONINKLIJKE PHILIPS N.V.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. A system for obtaining a confidence measure for a machine learning model, the system comprising:
an input interface configured to obtain input data;
a data modification component configured to generate a plurality of modified instances of the input data;
a machine learning model interface configured to communicate the input data and the plurality of modified instances of the input data to a machine learning model and further configured to receive a primary result generated by the machine learning model processing the input data and to receive a plurality of secondary results generated by the machine learning model processing the respective plurality of modified instances of the input data; and
an analysis component configured to determine a confidence measure relating to the primary result based on the secondary results, wherein the data modification component is configured to apply a first spatial warping transformation to the input data to generate a first modified instance of the input data, wherein the analysis component is configured to determine a measure of distribution or variance of the secondary results and to determine a confidence measure based on the determined measure of distribution or variance, wherein determining the measure of distribution or variance of the secondary results comprises determining at least one of:
the inverse variance of the secondary results;
the Shannon entropy of the secondary results;
the gini coefficient of the secondary results;
the Kullback-Liebler divergence of the secondary results; and
a concentration measure of the secondary results, wherein the data modification component is further configured to apply a first inverse spatial warping transformation to the secondary result generated for the first modified instance of the input data.