1. A method of predicting a computing value comprising the steps of: at least one computer: storing a training data set comprising past computing instances that include previously-executed processor operations, each past computing instance comprising attributes and a past computing value; separating the training data set into a predictable set of past computing instances and an unpredictable set of past computing instances, wherein separating the training data set into the predictable set and unpredictable set comprises: determining indications of error based on applying a predictability classifier to the training data set; using the indications of error to separate the training data set into the predictable set and the unpredictable set, wherein the unpredictable set is identified based on one of: identifying a predetermined percentile of the distribution of indications of error, and identifying indications of error that have a predetermined relation to a threshold; forming a predictor from the predictable set of past computing instances; and applying the predictor to a pending computing instance that meets a predictability test to determine a predicted value for the pending computing instance, wherein the predictability test includes applying a version of the predictability classifier to the pending computing instance.