def test_kmp_precomputed_dictionary():
n_samples = mult_dense.shape[0]
cv = ShuffleSplit(n_samples,
n_iterations=1,
test_fraction=0.2,
random_state=0)
train, test = list(cv)[0]
X_train, y_train = mult_dense[train], mult_target[train]
X_test, y_test = mult_dense[test], mult_target[test]
components = select_components(X_train, y_train,
n_components=0.3,
random_state=0)
K_train = pairwise_kernels(X_train, components)
kmp = KMPClassifier(metric="precomputed")
kmp.fit(K_train, y_train)
y_pred = kmp.predict(K_train)
acc = np.mean(y_pred == y_train)
assert_true(acc >= 0.75)
K_test = pairwise_kernels(X_test, components)
y_pred = kmp.predict(K_test)
acc = np.mean(y_pred == y_test)
assert_true(acc >= 0.63)
def test_kmp_fit_multiclass():
for metric, acc in (("rbf", 0.796),
("linear", 0.803),
("poly", 0.836)):
kmp = KMPClassifier(n_nonzero_coefs=4.0/5,
n_components=0.5,
n_refit=10,
metric=metric,
random_state=0)
kmp.fit(mult_dense, mult_target)
y_pred = kmp.predict(mult_dense)
assert_almost_equal(np.mean(mult_target == y_pred), acc, decimal=2)
def test_kmp_fit_binary_backfitting():
for metric, acc in (("rbf", 0.723),
("linear", 0.954),
("poly", 0.724)):
kmp = KMPClassifier(n_nonzero_coefs=1.0,
n_components=0.5,
n_refit=1,
metric=metric,
random_state=0)
kmp.fit(bin_dense, bin_target)
assert_equal(kmp.components_.shape[1], bin_dense.shape[0] / 2)
y_pred = kmp.predict(bin_dense)
assert_almost_equal(np.mean(bin_target == y_pred), acc, decimal=2)
try:
color = int(sys.argv[1])
except:
color = True
try:
surface = int(sys.argv[2])
except:
surface = False
X1, y1, X2, y2 = gen_non_lin_separable_data()
X_train, y_train = split_train(X1, y1, X2, y2)
X_test, y_test = split_test(X1, y1, X2, y2)
clf = KMPClassifier(n_nonzero_coefs=0.3,
n_components=1.0,
metric="rbf",
gamma=0.1,
n_refit=1,
estimator=Ridge(alpha=0.01),
random_state=random_state)
clf.fit(X_train, y_train)
y_predict = clf.predict(X_test)
correct = np.sum(y_predict == y_test)
print "%d out of %d predictions correct" % (correct, len(y_predict))
plot_contour(X_train, clf, color, surface)