8184b9fdf51e3f75835fe1f2d56c294d16686241,examples/federated_learning_with_encryption.py,,,#,162

Before Change



    // Each client trains a linear regressor on its own data
    for (i, c) in enumerate(clients):
        c = c.fit(X[i], y[i], n_iter=50, eta=0.05)
        print(c.weights)

    // Predict
    for (i, c) in enumerate(clients):

After Change


        clients[2].gradient_step(aggr)

    for (i, c) in enumerate(clients):
        y_pred = c.predict(c.X)
        print(mean_square_error(y_pred, c.y))

    for (i, c) in enumerate(clients):
        y_pred = c.predict(X_test)
        print(mean_square_error(y_pred, y_test))
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 4

Instances


Project Name: data61/python-paillier
Commit Name: 8184b9fdf51e3f75835fe1f2d56c294d16686241
Time: 2017-06-20
Author: giorgio.patrini@anu.edu.au
File Name: examples/federated_learning_with_encryption.py
Class Name:
Method Name:


Project Name: titu1994/DenseNet
Commit Name: 516c2a4c7e8f92e1ea299e966215c2ffe4c5b980
Time: 2016-12-07
Author: titu1994@gmail.com
File Name: cifar10.py
Class Name:
Method Name:


Project Name: data61/python-paillier
Commit Name: eb4ffb6cdaf6f04f978fc57e32c95c8b4a33bcb6
Time: 2017-06-20
Author: giorgio.patrini@anu.edu.au
File Name: examples/federated_learning_with_encryption.py
Class Name:
Method Name: