Transfer learning for regression problems I have trained a regression model with 7 features for a given problem.
Now, I have another regression problem (quite similar to the previous one) where I have only 6 samples in hand, but with 3 more features than the first model (7+3). The correlation between the target value and these 3 additional features is very high.
So I would like to use transfer learning method to create a new model based on the old model; but I can not find a way to integrate the additional features into the model, since the old one was trained only on X features. On the other hand I must employ the 3 additional features in the new model which means that I cannot just remove or ignore them.
Thanks.

One way: Use your old model's prediction as a new feature and combine with the additional three you have, i.e. a four-length feature vector for each sample. Then, train with these new features. So, the old model will act like a static feature generator for you. Of course, you may have challenges with that low number of samples.
