  The area of transfer learning comprises supervised machine learning methods
that cope with the issue when the training and testing data have different
input feature spaces or distributions. In this work, we propose a novel
transfer learning algorithm called Renewing Iterative Self-labeling Domain
Adaptation (Re-ISDA). In this work, we propose a novel transfer learning
algorithm called Renewing Iterative Self-labeling Domain Adaptation (Re-ISDA).
