| CPC G06N 3/006 (2013.01) [G06N 20/00 (2019.01)] | 23 Claims |
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1. A computer system comprising:
one or more processing devices and at least one memory device operably coupled to the one or more processing devices, the one or more processing devices are configured to:
receive input data directed toward one or more subjects of interest;
determine a plurality of objectives to be optimized;
ingest at least a portion of the input data through one or more machine learning (ML) models;
apply a weight to each of the plurality of objectives, thereby to generate a plurality of weighted objectives, thereby to generate a plurality of weighted aggregated single objectives;
determine a plurality of Pareto optimal solutions, thereby defining a plurality of ML pipelines that optimize the plurality of weighted aggregated single objectives, wherein the Pareto optimal solutions are utilized to graphically define a Pareto-front curve which is displayed to a user in a graphical user interface;
identify at least a portion of the Pareto-front curve to be refined based on a plurality of additional constraints identified by the user by selecting at least a portion of the Pareto-front curve in the graphical user interface for at least one or more of the plurality of objectives to be optimized;
determine whether the plurality of additional constraints identified are supported or not supported for generating a plurality of additional single objective optimizations without modifying the plurality of weighted aggregated single objectives;
determine a plurality of additional Pareto-optimal solutions, wherein the Pareto-front curve is refined based on the plurality of additional Pareto-optimal solutions; and
select one ML pipeline from the plurality of ML pipelines.
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