eb4ffb6cdaf6f04f978fc57e32c95c8b4a33bcb6,examples/federated_learning_with_encryption.py,,,#,203

Before Change

    clients.append(Client("Carol", server.pubkey))

    c = clients[0]
    c.fit(X[0], y[0], n_iter=60, eta=0.1)
    print("Train", mean_square_error(c.predict(X[0]), y[0]))
    print("Test", mean_square_error(c.predict(X_test), y_test))

    // Each client trains a linear regressor on its own data

After Change

    print(aggr)
    for (i, c) in enumerate(clients):
        c.weights = aggr
        y_pred = c.predict(X_test)
        print(mean_square_error(y_pred, y_test))

Instances