1. A method comprising: processing a training dataset by one or more computing devices using an iterative algorithm having a cost function, the processing including for a plurality of iterations of the iterative algorithm, computing: a cost for the iterative algorithm using the cost function; and a value for each of a plurality of performance metrics that are usable to infer accuracy of the iterative algorithm for a respective said iteration; responsive to the processing, identifying a stopping criterion based at least in part on the computed values for the plurality of performance metrics; and outputting the stopping criterion to configure the iterative algorithm to use the stopping criterion for subsequent processing of data by the iterative algorithm.