Our approach works as follows: in training, we first use an empirical domain difference testing method to detect whether two groups of data should be considered as different domains; after that we apply supervised clustering to learn the distance metric between two data points, i.e.
our FEDA methods use L 2 -regularized SVM with linear kernel by LIBLINEAR package 1 .