1. A training system to train at least a first machine learning system of a candidate selection system, the training system comprising: at least one non-transitory processor-readable medium that stores processor-executable instructions; and at least one processor communicably coupled to the at least one non-transitory processor-readable medium and which executes the processor-executable instructions and in response: identifies from a plurality of entities a first entity and a second entity that are a historically successful pairing based at least in part on an absence of both the first and the second entities from candidate selection system for a defined period of time, each of the plurality of entities associated with a plurality of attributes; generates a plurality of hypothetical entities, each of the hypothetical entities based on the second entity in the historically successful pairing, and each of the hypothetical entities having a plurality of attributes which are based on a corresponding plurality of attributes for the second entity upon which the hypothetical entity is based, at least one attribute of the plurality of attributes of the hypothetical entity modified to be different from the corresponding attribute of the first entity in the successful pairing; generates a plurality of hypothetical alternative pairings, each of the plurality of hypothetical alternative pairings comprising: an alternative pairing between the first entity and one of the plurality of hypothetical entities based on the second entity; provides the first machine learning system of the candidate selection system with the historically successful pairing as one training example; and provides the first machine learning system of the candidate selection system with at least one of the hypothetical alternative pairings as an additional training example.