Learn on Source, Refine on Target:A Model Transfer Learning Framework with Random Forests

Noam Segev, Maayan Harel, Shie Mannor +2

We propose novel model transfer-learning methods that refine a decision forest model M learned within a "source" domain using a training set sampled from a "target" domain, assumed…