US 12,086,721 B1
System and methods for an adaptive machine learning model selection based on data complexity and user goals
Barbara Sue Smith, Toronto (CA); and Daniel J. Sullivan, Toronto (CA)
Filed by The Strategic Coach Inc., Toronto (CA)
Filed on Mar. 8, 2024, as Appl. No. 18/600,487.
Int. Cl. G06N 3/092 (2023.01); G06N 3/088 (2023.01); G06N 3/0895 (2023.01); G06N 3/09 (2023.01)
CPC G06N 3/092 (2023.01) [G06N 3/088 (2013.01); G06N 3/0895 (2023.01); G06N 3/09 (2023.01)] 20 Claims
OG exemplary drawing
 
1. An apparatus for an adaptive machine learning model selection based on data complexity and user goals, wherein the apparatus comprises:
at least a processor; and
a memory communicatively connected to the at least a processor, wherein the memory containing instructions configuring the at least a processor to:
generate a first model as a function of a first dataset and a first set of analytic goals;
determine a complexity metric of a second dataset;
compare the complexity metric with a predetermined threshold, wherein the level of complexity comprises a scale of threshold;
identify a first complexity gap as a function of the comparison and the first model;
generate a plurality candidate features of the second dataset using a feature learning algorithm;
generate at least a second model using the plurality of candidate features;
identify a second complexity gap as a function of the at least a second model using a third dataset; and
select the at least a second model as a function of the second complexity gap.