def test_naive_asgd_with_feedback(): n_points = 1e3 n_features = 1e2 X, y = get_fake_data(n_points, n_features, 42) Xtst, ytst = get_fake_data(n_points, n_features, 43) clf = ASGD(n_features, sgd_step_size0=1e-3, l2_regularization=1e-6, n_iterations=4, feedback=True, dtype=np.float32) clf.fit(X, y) ytrn_preds = clf.predict(X) ytst_preds = clf.predict(Xtst) ytrn_acc = (ytrn_preds==y).mean() ytst_acc = (ytst_preds==y).mean() assert_equal(ytrn_acc, 0.707) assert_equal(ytst_acc, 0.505)
def test_naive_asgd(): rstate = RandomState(42) X, y = get_fake_data(N_POINTS, N_FEATURES, rstate) Xtst, ytst = get_fake_data(N_POINTS, N_FEATURES, rstate) clf = BinaryASGD(*DEFAULT_ARGS, rstate=rstate, **DEFAULT_KWARGS) clf.fit(X, y) ytrn_preds = clf.predict(X) ytst_preds = clf.predict(Xtst) ytrn_acc = (ytrn_preds == y).mean() ytst_acc = (ytst_preds == y).mean() assert_equal(ytrn_acc, 0.72) assert_equal(ytst_acc, 0.522)
def test_naive_asgd_with_feedback(): raise SkipTest("FIXME: feedback support is buggy") rstate = RandomState(43) X, y = get_fake_data(N_POINTS, N_FEATURES, rstate) Xtst, ytst = get_fake_data(N_POINTS, N_FEATURES, rstate) clf = BinaryASGD(*DEFAULT_ARGS, feedback=True, rstate=rstate, **DEFAULT_KWARGS) clf.fit(X, y) ytrn_preds = clf.predict(X) ytst_preds = clf.predict(Xtst) ytrn_acc = (ytrn_preds == y).mean() ytst_acc = (ytst_preds == y).mean() assert_equal(ytrn_acc, 0.709) assert_equal(ytst_acc, 0.449)