CPC G06N 20/00 (2019.01) [G05B 23/024 (2013.01); G06F 17/16 (2013.01); G06F 17/18 (2013.01); G06F 30/27 (2020.01); G06F 2111/10 (2020.01); G06N 3/08 (2013.01); G06N 20/10 (2019.01)] | 20 Claims |
1. A computer-implemented method for auditing the results of a machine learning model, the method comprising:
retrieving a set of state estimates for original time series data values from a database under audit, wherein the each of the state estimates is generated by a state estimation computation for one of the time series data values;
reversing the state estimation computation for each of the state estimates to produce reconstituted time series data values for each of the state estimates;
retrieving the original time series data values from the database under audit;
comparing the original time series data values pairwise with the reconstituted time series data values to determine whether the original time series and reconstituted time series match; and
generating a signal that the database under audit (i) has not been modified where the original time series and reconstituted time series match, and (ii) has been modified where the original time series and reconstituted time series do not match.
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