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Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing machine learning systems. In one aspect a method includes determining an average error of a machine learning system (“MLS”). An evaluation function that provides a result that would have been achieved using a specified value of a given parameter is defined. An expected outcome function that provides expected results for prior events based on the error of the MLS is defined. For each of multiple prior events, a target value of the given parameter is determined, eg, using the expected outcome function. A model is generated using the MLS based on features of the prior events and the determined target values of the given parameter for the prior events. A value is assigned to the given parameter for a new event based on application of the model to features of the new event.