1. A method, comprising: defining a reference model of a system for modeling data associated with the system, the reference model having a plurality of terms; generating a reference fit error metric for the reference model; generating a set of evaluation models each having one term different than the reference model; generating an evaluation fit error metric for each of the evaluation models; replacing the reference model with a selected evaluation model responsive to the selected evaluation model having an evaluation fit error metric less than the reference fit error metric; repeating, based on the replaced reference model, the generating of the reference fit error metric, the generating of the set of evaluation models, the generating of the evaluation fit error metrics, and the replacing of the reference model until no evaluation model has an evaluation fit error metric less than the reference fit error metric; training the reference model in which no evaluation model has a smaller evaluation fit metric by using the data associated with the system; and employing the trained reference model to determine at least one characteristic of the system.
1. A method, comprising: defining a reference model of a system for modeling data associated with the system, the reference model having a plurality of terms; generating a reference fit error metric for the reference model; generating a set of evaluation models each having one term different than the reference model; generating an evaluation fit error metric for each of the evaluation models; replacing the reference model with a selected evaluation model responsive to the selected evaluation model having an evaluation fit error metric less than the reference fit error metric; repeating, based on the replaced reference model, the generating of the reference fit error metric, the generating of the set of evaluation models, the generating of the evaluation fit error metrics, and the replacing of the reference model until no evaluation model has an evaluation fit error metric less than the reference fit error metric; training the reference model in which no evaluation model has a smaller evaluation fit metric by using the data associated with the system; and employing the trained reference model to determine at least one characteristic of the system. 6. The method of claim 1 , wherein generating the set of evaluation models comprises generating a subset of the evaluation models by removing selected terms in the reference model, each removal generating one of the evaluation models.