| CPC G06F 16/256 (2019.01) [G06F 16/217 (2019.01); G06N 20/20 (2019.01); G06Q 50/16 (2013.01)] | 16 Claims |
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1. A computer-implemented method comprising:
obtaining model data input to a first machine learning model in a plurality of machine learning models used in a property valuation workflow or output from the first machine learning model;
applying the model data as an input to at least one of a plurality of machine learning anomaly detection models, wherein the at least one of the plurality of machine learning anomaly detection models is different than the first machine learning model;
detecting an anomaly in the model data applied as the input to the at least one of the plurality of machine learning anomaly detection models based on an output of the at least one of the plurality of machine learning anomaly detection models;
generating a suggestion to modify at least some of the model data based on a profile associated with the detected anomaly, wherein the suggestion comprises an identification of the detected anomaly;
presenting the suggestion to a user for review;
modifying the at least some of the model data in accordance with the generated suggestion; and
re-training the first machine learning model using the modified at least some of the model data.
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