def test_binary_sgd_step_size0(): rstate = RandomState(42) n_features = 20 X, y = get_fake_data(100, n_features, rstate) clf = get_new_model(n_features, rstate) best = find_sgd_step_size0(clf, X, y, (.25, .5)) assert_almost_equal(best, -4.9927, decimal=4) # start a little lower, still works best = find_sgd_step_size0(clf, X, y, (.125, .25)) assert_almost_equal(best, -4.6180, decimal=4) # find_sgd_step_size0 does not change clf assert clf.sgd_step_size0 == 1000.0
def test_binary_fit(): rstate = RandomState(42) n_features = 20 for L in [100, DEFAULT_MAX_EXAMPLES, int(DEFAULT_MAX_EXAMPLES * 1.5), int(DEFAULT_MAX_EXAMPLES * 3)]: clf = get_new_model(n_features, rstate, L) X, y = get_fake_data(L, n_features, rstate, separation=0.1) best = find_sgd_step_size0(clf, (X, y)) _clf = binary_fit(clf, (X, y)) assert _clf is clf assert 0 < clf.sgd_step_size0 <= best
def test_binary_sgd_step_size0(): rstate = RandomState(42) n_features = 20 X, y = get_fake_data(100, n_features, rstate) clf = get_new_model(n_features, rstate, 100) best0 = find_sgd_step_size0(clf, (X, y)) print best0 assert np.allclose(best0, 0.04, atol=.1, rtol=.5) # find_sgd_step_size0 does not change clf assert clf.sgd_step_size0 == 1000.0