This is due to the heavily biased class distribution in our collection: global model puts great emphasis on the positive reviews; while the adaptation methods give equal weights to both positive and negative reviews.
in LinAdapt, scaling and shifting operations lead to satisfactory adaptation performance for the negative class with only 15 reviews; while rotation is essential for recognizing the positive class.