| CPC G06F 40/40 (2020.01) [G06F 40/284 (2020.01)] | 30 Claims |
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1. A method comprising:
receiving, by at least one hardware processor, results generated by a machine learning (ML) model, the results including at least one confidence score;
enabling high selective prediction accuracy of the results generated by the ML model configured to perform document processing and understanding of an electronic text document;
implementing confidence scoring recalibration to address at least one challenge, the confidence scoring recalibration including functionality to assess reliability of the results generated by the ML model;
applying post-processing calibration to the at least one confidence score generated by the confidence scoring recalibration to enhance performance of the ML model, the post-processing calibration including adjusting the at least one confidence score generated by the confidence scoring recalibration;
based on the adjusting of the at least one confidence score, extracting individual elements of information from the electronic text document, the extracted individual elements of the information including one or more extracted values; and
storing the one or more extracted values in a database including an adjusted confidence score associated with each of the one or more extracted values and the results generated by a ML model.
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