Technologies are generally described for methods and systems in a machine learning environment. In some examples, a method may include retrieving training data from a memory. The training data may include training inputs and training labels. The methods may further include determining a set of datasets based on the training inputs. The methods may further include determining a set of out of sample errors based on the training inputs and based on test data. Each out of sample error may correspond to a respective dataset in the set of datasets. The methods may further include generating alternative distribution data based on the set of out of sample errors. The alternative distribution data may be used to determine weights to be applied to the training data.