1. A method, in a data processing system comprising a processor and a memory, for configuring a ranker array of a question and answer (QA) system, comprising: generating, by the data processing system, an initial configuration of the ranker array of the QA system, wherein the ranker array comprises a plurality of rankers, and wherein each ranker in the ranker array applies a statistical classification function to candidate answers generated by the QA system in response to an input question to generate a ranked listing of candidate answers for the ranker; inputting, by the data processing system, a training question to the QA system to generate a training candidate answer set; applying, by the data processing system, the ranker array to the training candidate answer set to generate, for each ranker in the ranker array, a corresponding ranked listing of candidate answers in the training candidate answer set; determining, by the data processing system, for each ranker in the ranker array, correctness of the corresponding ranked listing of candidate answers; and reconfiguring, by the data processing system, the ranker array based on results of the determined correctness of the corresponding ranked listing of candidate answers for each ranker in the ranker array, wherein the generating, inputting, applying, determining, and reconfiguring operations are performed iteratively over a plurality of training iterations, and wherein, for each training iteration in the plurality of training iterations, at least one of the training questions or a sampling of a corpus of data upon which the training questions or ranker array operates is different from other training iterations in the plurality of training iterations.
1. A method, in a data processing system comprising a processor and a memory, for configuring a ranker array of a question and answer (QA) system, comprising: generating, by the data processing system, an initial configuration of the ranker array of the QA system, wherein the ranker array comprises a plurality of rankers, and wherein each ranker in the ranker array applies a statistical classification function to candidate answers generated by the QA system in response to an input question to generate a ranked listing of candidate answers for the ranker; inputting, by the data processing system, a training question to the QA system to generate a training candidate answer set; applying, by the data processing system, the ranker array to the training candidate answer set to generate, for each ranker in the ranker array, a corresponding ranked listing of candidate answers in the training candidate answer set; determining, by the data processing system, for each ranker in the ranker array, correctness of the corresponding ranked listing of candidate answers; and reconfiguring, by the data processing system, the ranker array based on results of the determined correctness of the corresponding ranked listing of candidate answers for each ranker in the ranker array, wherein the generating, inputting, applying, determining, and reconfiguring operations are performed iteratively over a plurality of training iterations, and wherein, for each training iteration in the plurality of training iterations, at least one of the training questions or a sampling of a corpus of data upon which the training questions or ranker array operates is different from other training iterations in the plurality of training iterations. 2. The method of claim 1 , wherein reconfiguring the ranker array based on results of the determined correctness comprises: generating a ranker array reward value for the ranker array based on the correctness of the corresponding ranked listing of candidate answers for each of the rankers in the ranker array; comparing the ranker array reward value to a reward value threshold value; and reconfiguring the ranker array in response to the ranker array reward value not satisfying a predetermined relationship with regard to the reward value threshold value.