Federated learning (FL, also known as distributed learning) algorithms try to learn a global model using data from different sources without data ever leaving their original location. Furthermore, no raw (patient) sensitive data are shared between any of the parties. In other words, instead of bringing the data to the algorithms, we bring the algorithms to the data.
In this repository, we provide a FL implementation of a Generalized Linear Model (GLM). It can be easily used with VANTAGE6