12. An apparatus comprising: a processor; and memory including instructions that, when executed by the processor, cause the processor to: receive data associated with a domain input; determine statistical characteristics associated with one or more features of the domain input to generate feature statistical characteristics; identify, based on the generated feature statistical characteristics, a plurality of learned models, each of the plurality of learned models being associated with a respective other domain input, each respective other domain input being different than the domain input; compare the generated feature statistical characteristics with respective statistical characteristics associated with one or more features of the plurality of learned models; identify, based on the comparison, at least one learned model of the plurality of learned models that satisfies a threshold value; modify the identified at least one learned model to create at least one trained model, the at least one trained model being different than each of the at least one learned model, and the processor, when modifying the identified at least one learned model, is further to: analyze the respective statistical characteristics associated with the one or more features of the identified at least one learned model; and modify a portion of the respective statistical characteristics associated with the one or more features of the identified at least one learned model that corresponds to the generated feature statistical characteristics associated with the domain input; and use the at least one trained model as a domain model to process the received data.
12. An apparatus comprising: a processor; and memory including instructions that, when executed by the processor, cause the processor to: receive data associated with a domain input; determine statistical characteristics associated with one or more features of the domain input to generate feature statistical characteristics; identify, based on the generated feature statistical characteristics, a plurality of learned models, each of the plurality of learned models being associated with a respective other domain input, each respective other domain input being different than the domain input; compare the generated feature statistical characteristics with respective statistical characteristics associated with one or more features of the plurality of learned models; identify, based on the comparison, at least one learned model of the plurality of learned models that satisfies a threshold value; modify the identified at least one learned model to create at least one trained model, the at least one trained model being different than each of the at least one learned model, and the processor, when modifying the identified at least one learned model, is further to: analyze the respective statistical characteristics associated with the one or more features of the identified at least one learned model; and modify a portion of the respective statistical characteristics associated with the one or more features of the identified at least one learned model that corresponds to the generated feature statistical characteristics associated with the domain input; and use the at least one trained model as a domain model to process the received data. 21. The apparatus of claim 12 , where the processor is further to: analyze another domain input based on the domain model.