def METHOD_NAME():
    lr = LogisticRegression(
        eta=0.01, epochs=100, minibatches=len(y), l2_lambda=1.0, random_seed=1
    )
    lr.fit(X, y)
    y_pred = lr.predict(X)
    expect_weights = np.array([[0.24], [0.35]])
    np.testing.assert_almost_equal(lr.w_, expect_weights, 2)
    y_pred = lr.predict(X)
    acc = np.sum(y == y_pred, axis=0) / float(X.shape[0])
    assert acc == 0.97, "Acc: %s" % acc