1. A method in a machine learning environment, the method comprising: identifying, by a processor, a training distribution of a training data; identifying, by the processor, information about a test distribution of a test data; identifying, by the processor, a coordinate of the training data and the test data; determining, by the processor, for the coordinate, differences between the test distribution and the training distribution; and determining, by the processor, weights based on the differences, wherein the weights are adapted to cause the training distribution to conform to the test distribution when the weights are applied to the training distribution.