1. A system for performing a selection task using a decision neural network-based classifier, comprising: a memory storing a plurality of processor-executable instructions for training and operating the decision neural network-based classifier; and a processor that reads the plurality of processor-executable instructions from the memory to perform operations comprising: constructing a decision training set for the decision neural network-based classifier by: identifying, based on a confusion matrix generated from performance of a non-recurrent network-based classifier and a recurrent neural network-based classifier, a first subset of inputs inferred by the recurrent neural network-based classifier and a second subset of inputs comprising inputs not in the first subset, and including, in the decision training set, the first subset of inputs labeled with a first model class label identifying the recurrent neural network-based classifier and the second subset of inputs labeled with a second model class label identifying the non-recurrent neural network-based classifier; generating, by the decision neural network based classifier, a plurality of selection outputs in response to inputs from the decision training set; computing a training objective by comparing the plurality of selection outputs with labels from the first subset and the second subset; and updating the decision neural network based classifier based on the training objective wherein the operations further comprise: training the non-recurrent and recurrent neural network-based classifiers to perform the machine classification task using a training set, the training set comprising training inputs annotated with task class labels defined for the machine classification task; using the trained non-recurrent and recurrent neural network-based classifiers to perform the machine classification task on a validation set, the validation set comprising validation inputs annotated with the task class labels; and