1. A server-device-implemented method for optimizing training data for developing a predictive model to automatically value a subject real-estate property, the method comprising: obtaining, by said server device, an indication to provide an automated value prediction for the subject real-estate property as of an effective date; in response to obtaining said indication, defining, by said server device, a search space having multiple dimensions, each corresponding to a range of candidate values for a search criterion for selecting subsets of a multiplicity of sales-transaction records, said multiple dimensions including at least a temporal dimension that measures distance in time before the effective date, and a geographic dimension that measures distance in space away from the subject real-estate property; evaluating, by said server device, a multiplicity of points within said multi-dimension search space according to a statistical measure of model accuracy, said multiplicity of points varying along at least said temporal dimension and said geographic dimension; selecting, by said server device based at least in part on evaluating said multiplicity of points within said multi-dimension search space, an accuracy-optimized subset of said multiplicity of sales-transaction records; and developing, by said server device, the predictive model according to said accuracy-optimized subset of said multiplicity of sales-transaction records to generate said automated value prediction for the subject real-estate property as of the effective date.