Kernel Mean Matching implementation It is implementation of correcting sample selection bias by unlabeled Data paper, published on nips 2007, referred as sample selection bias or kernel mean matching, which represent the problem as a optimization problem, and find the sample weights in source domain to be matched with the target domain without estimating the distribution.