transfer Learning in regression for similar domain but different distr

Question

I am currently working on a KDD project aiming to build a predictor with very small real world data. The goal is to predict to predict the quantity Y of an instance of an Product while knowing other quantities of this instance. There are Predictors (same Task) trained on similar (not the same) products. Those Models are valid for their use-case.

My approach is to use large datasets of other products (similar domain, similar task but different distributions) and adapt those to the target domain using transfer Learning.

At this pint I am having trouble finding methods/algorithms fitting my needs. Looking at the decision tree 1 it should be a domain adaption problem.

What algorithm or Model is suited for this kind of usecase?

question from:https://stackoverflow.com/questions/65922056/transfer-learning-in-regression-for-similar-domain-but-different-distr

Answer 1

Waitting for answers