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vantage6

A privacy preserving federated learning solution


v6-colnames-py

This algoithm is part of the vantage6 solution. Vantage6 allowes to execute computations on federated datasets. This contains the code for the v6-colnames-py algorithm, which returns the column names of all the nodes in a collaboration.

Running the train

This will mainly depend on how the infrastructure has been set up - the correct URLs have to be entered and login details need to be correct. As an example, the run.py file has been provided. This has been taken from this repository, which also contains an example infrastructure that can be used to simulate a real-world scenario (it also works with the example method.py file provided). The details in the run.py file are in place to use this sample infrastructure and have to be changed for a production environment. As can be see in this local run.py, no (kw)args are needed to run this algorithm. Then simply run the file using:

python run.py

The output of this algorithm is a dictionary, with one key for each of the nodes (e.g. node1, node2), and one key for a set with the intersection of all column names present in the nodes. This set is useful to make sure that the algorithm you're running will have the appropriate data available on each of the nodes.

Read more

See the documentation for detailed instructions on how to install and use the server and nodes.


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