1. A method of selecting a profile model for use in examining a structure formed on a semiconductor wafer using optical metrology, the method comprising: a) obtaining an initial profile model having a set of profile parameters that characterize the structure to be examined; b) training a machine learning system using the initial profile model; c) generating a simulated diffraction signal for an optimized profile model using the trained machine learning system, wherein the optimized profile model has a set of profile parameters with the same or fewer profile parameters than the initial profile model; and d) modifying the optimized profile model by eliminating at least one profile parameter or fixing to a value at least one profile parameter and iterating steps c) and d) using the modified optimized profile model and the same trained machine learning system until one or more termination criteria are met.
1. A method of selecting a profile model for use in examining a structure formed on a semiconductor wafer using optical metrology, the method comprising: a) obtaining an initial profile model having a set of profile parameters that characterize the structure to be examined; b) training a machine learning system using the initial profile model; c) generating a simulated diffraction signal for an optimized profile model using the trained machine learning system, wherein the optimized profile model has a set of profile parameters with the same or fewer profile parameters than the initial profile model; and d) modifying the optimized profile model by eliminating at least one profile parameter or fixing to a value at least one profile parameter and iterating steps c) and d) using the modified optimized profile model and the same trained machine learning system until one or more termination criteria are met. 7. The method of claim 1 , wherein the one or more termination criteria includes a sensitivity determined for a profile parameter of the optimized profile model.