test_logistic.py 文件源码

 复制代码def test_liblinear_dual_random_state():
    # random_state is relevant for liblinear solver only if dual=True
    X, y = make_classification(n_samples=20)
    lr1 = LogisticRegression(random_state=0, dual=True, max_iter=1, tol=1e-15)
    lr1.fit(X, y)
    lr2 = LogisticRegression(random_state=0, dual=True, max_iter=1, tol=1e-15)
    lr2.fit(X, y)
    lr3 = LogisticRegression(random_state=8, dual=True, max_iter=1, tol=1e-15)
    lr3.fit(X, y)

    # same result for same random state
    assert_array_almost_equal(lr1.coef_, lr2.coef_)
    # different results for different random states
    msg = "Arrays are not almost equal to 6 decimals"
    assert_raise_message(AssertionError, msg,
                         assert_array_almost_equal, lr1.coef_, lr3.coef_)