In this example we demonstrate how to use SVMs in a domain adaptation
scenario. Here, we assume that we have two problem domains, one with
an abundance of training data (source domain) and one with only a few
training examples (target domain). These domains are assumed to be
different but related enough to transfer information between them.
Thus, we first train an SVM on the source domain and then subsequently
pass this previously trained SVM object to the DASVM, that we train
on the target domain. The DASVM internally computes a custom linear term
(for the underlying quadratic program of the dual formulation of the SVM)
based on the support vectors of the source SVM and the training examples
of the target SVM. Finally, it can be used for prediction just as any other
SVM object.

