1. A method, in a machine learning system comprising a plurality of learned models uniquely corresponding to a plurality of domains, for determining which of the plurality of learned models to use as a basis for a new domain model, the method comprising: determining, by a processing device, statistical characteristics of features in new domain input to provide new feature statistical characteristics, wherein the new domain input is provided for training the new domain model; comparing, by the processing device, the new feature statistical characteristics with statistical characteristics of at least some of the plurality of learned models; and identifying, by the processing device, at least one learned model of the plurality of learned models as the basis for the new domain model when the new feature statistical characteristics compare favorably with the statistical characteristics of the features in the prior input corresponding to the at least one learned model.