def test_debiasing_warm_start():
clf = PrimalSVC(kernel="rbf", gamma=0.1, penalty="l1", max_iter=10)
clf.C = 0.5
clf.fit(bin_dense, bin_target)
assert_equal(clf.n_support_vectors(), 160)
assert_almost_equal(clf.score(bin_dense, bin_target), 0.845)
clf = PrimalSVC(kernel="rbf", gamma=0.1, penalty="l1", max_iter=10)
clf.C = 0.500001
clf.fit(bin_dense, bin_target)
assert_equal(clf.n_support_vectors(), 191)
assert_almost_equal(clf.score(bin_dense, bin_target), 0.97)
clf = PrimalSVC(kernel="rbf", gamma=0.1, penalty="l1", max_iter=10,
warm_start=True)
clf.C = 0.5
clf.fit(bin_dense, bin_target)
assert_equal(clf.n_support_vectors(), 160)
assert_almost_equal(clf.score(bin_dense, bin_target), 0.845)
clf = PrimalSVC(kernel="rbf", gamma=0.1, penalty="l1", max_iter=10,
warm_start=True)
clf.C = 0.500001
clf.fit(bin_dense, bin_target)
assert_equal(clf.n_support_vectors(), 191)
assert_almost_equal(clf.score(bin_dense, bin_target), 0.97)
def test_warm_start_l2r_rbf():
clf = PrimalSVC(warm_start=True, kernel="rbf", gamma=0.1,
random_state=0, penalty="l2")
clf.C = 0.1
clf.fit(bin_dense, bin_target)
assert_almost_equal(clf.score(bin_dense, bin_target), 1.0)
clf.C = 0.2
clf.fit(bin_dense, bin_target)
assert_almost_equal(clf.score(bin_dense, bin_target), 1.0)
def test_warm_start_l1r_rbf():
clf = PrimalSVC(warm_start=True, kernel="rbf", gamma=0.1,
random_state=0, penalty="l1")
clf.C = 0.5
clf.fit(bin_dense, bin_target)
n_nz = np.sum(clf.coef_ != 0)
clf.C = 0.6
clf.fit(bin_dense, bin_target)
n_nz2 = np.sum(clf.coef_ != 0)
assert_true(n_nz < n_nz2)
def test_shared_kcache():
clf = PrimalSVC(warm_start=True, kernel="rbf", gamma=0.1,
random_state=0, penalty="l1")
kernel = get_kernel("rbf", gamma=0.1)
kcache = KernelCache(kernel, bin_dense.shape[0], 10, 1, 0)
clf.C = 0.5
clf.fit(bin_dense, bin_target, kcache=kcache)
n_nz = np.sum(clf.coef_ != 0)
clf.C = 0.6
clf.fit(bin_dense, bin_target, kcache=kcache)
n_nz2 = np.sum(clf.coef_ != 0)
assert_true(n_nz < n_nz2)
