1. A method for selecting a predictive model for a prediction problem, the method comprising: determining suitabilities of a plurality of predictive modeling procedures for the prediction problem based, at least in part, on characteristics of the prediction problem and/or on attributes of the respective modeling procedures, wherein, for each of the predictive modeling procedures, the determined suitability of the predictive modeling procedure for the prediction problem comprises a value representing an estimated performance of a predictive model generated using the predictive modeling procedure and applied to the prediction problem; selecting at least a subset of the predictive modeling procedures based, at least in part, on the determined suitabilities of the selected modeling procedures for the prediction problem; transmitting instructions to a plurality of processing nodes, the instructions comprising a resource allocation schedule allocating resources of the processing nodes for execution of the selected modeling procedures based, at least in part, on the determined suitabilities of the selected modeling procedures for the prediction problem, wherein the resource allocation schedule allocates different portions of the resources of the processing nodes to different subsets of the selected modeling procedures in accordance with the determined suitabilities of the selected modeling procedures; receiving results of the execution of the selected modeling procedures by the plurality of processing nodes in accordance with the resource allocation schedule, wherein the results include predictive models generated by the selected modeling procedures, and/or scores of the models for data associated with the prediction problem; and selecting, from the predictive models, a predictive model for the prediction problem based, at least in part, on the score of the selected predictive model.